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1. The software uses its SGML parser see above to read XML files Extensible Markup Language The same limitations are also applicable to this format The conversion engine does not interpret scripts or style sheets Microsoft Word SGML e e The conversion of PDF documents may require the installation of an Adobe IFilter component on your system You can download the latest version of filter on Adobe s site http www adobe com support downloads detail jsp ftplD 261 1 Note that the addition of this component does not require installation of Adobe Reader The software uses the current IFilter components installed on your system to convert Microsoft Word documents In case of problems corrupted file etc conversion automatically switches over to binary analysis heuristic which attempts to recover the www semantic knowledge com 61 Tropes Reference Manual text by binary origin If you notice that the software jams on certain Word files you can deactivate conversion using the Analysis options dialog tab sheet Conversions It is never possible for password protected files to be read and directly converted by the software These files must be converted manually for analysis When the software performs a binary analysis heuristic to extract the text parasitic characters may appear By definition this method of origin of the text cannot be perfect because the software does not take into account the native fi
2. you may use it to split up the utterances into several files each file containing for example the utterances corresponding to only one variable that you can analyze separately in order to compare them You can also code these variables inside the texts and then use them as Borders If the corpus has no linear coherence for example when the utterances contained in each file have been compiled at random without following a particular logic the results depending on the chronological analyses of Tropes Most Characteristic Parts of text Bundles Episodes Distribution graphs will not be significant do not try to interpret these results www semantic knowledge com 57 Tropes Reference Manual Analysis of discourses and conversations When analyzing a text file containing the transcript of the discourse of several individuals start with an overall analysis of the corpus then use Borders to process the utterances of the various characters separately and compare the results obtained When comparing the results ask yourself the following questions have all the participants been talking about the same thing Did they use the same Actants If not then why not Has anyone refused to reply to certain questions Has anyone been trying to convince another participant Why Have they succeeded Etc If you have time you can solve the anaphoras manually i e replace each personal pronoun by who it refers to Let us imagine for example
3. that you wish to analyze the discourse of two characters Petre and Paul who have been talking about three other persons Alin Maria and lulia and that the text contains many personal pronouns eu tu el ea etc Use the find replace command of your word processor to replace some of these pronouns as follows eu and tu by Petre or Paul ea by Maria or lulia el by Alin etc You will thus be able to count very precisely how many times this or that person has been mentioned to know whether they are Actants or Acted etc When you make transcripts from the spoken form it is necessary that you include punctuation in the text otherwise the software will not be able to carry out the propositional hashing properly and the processing of the analysis will be altered Literary studies To analyze a play use the above method analyzing the utterances of multiple actors is almost equivalent to analyzing a conversation between different interlocutors When studying long texts such as an entire book first analyze each chapter separately then you can make a synthesis by processing the whole text see Reflections on the size of the texts above www semantic knowledge com 58 Tropes Reference Manual Comparing two texts Comparing two texts comes down to making an analysis both of the contents i e of the Equivalent classes and of the Setting i e of the word ca
4. To view the content of a class click on this class and all the words that comprise it will then be displayed in red in the main window Actants and Acted This option enables you to tell the position of the Reference fields higher level Equivalent classes and of the References lower level Equivalent classes see below both being generally placed either as Actant i e before the verb and often subject of this verb or as Acted i e after the verb Results Explain Extract Files Ej Text style A B Cu br tara si cu parfumul acea de neuitat mireasm de garoafa rosie inelele YY Reference fields 1 E erau singurele lucruri ul Reference fields 2 garoafe i orhidee rare un adev rat desfr ui i n a fi avut cum cuno team pe domnisoara v nz toare Ej Relations ASS MUN a ea a ca E MORE E s o Y Frequent word categories urm resc Mai imb t toare ca orice b utur m inv luia o aprig mireasma de garoafa care se desprindea de la o coconit a ezat la masa de alaturi mireasma Y M Actant Acted 0004 75 garoaf 0004 7596 imprejurare 0003 10096 inceput 0004 5096 inel 0004 5096 istorie When checking one of these boxes only the list shows the number of times percentage between parentheses the corresponding c ass has been in the position of Actant in the studied text The same counter will appear when you print the c asses list To get back to the standard di
5. Word category that tend to appear in a remarkable density within a limited portion of the text somewhere near the beginning the middle or the end but not on a regular pattern throughout the whole text an Episode corresponds to a part of the text in which a number of Bundles have been formed and completed These are large blocks of arguments quite representative of the structure of the discourse studied Episodes are displayed one after the other and numbered according to their occurrence order Inside each Episode Bundles are sorted out according to their address words position average and prefixed by the occurrence frequency of the words that comprise each Bundle For example the Remember txt text begins with a first Episode including short Bundles about the sear muzeu t n r References but also connectors modalities Then comes a second Episode including a rather long Bundle beginning in the first Episode about fat containing 4 words etc The text ends with Bundles about istorie This analysis brings out the construction of the discourse by the narrator who starts his narrative in this case a short story by talking about sear muzeu t n r before speaking of lume neam and inel and then ending his discourse by talking of noapte canal Aubrey de Vere istorie etc Important note different Bundles about an identical Reference may
6. appear in various parts of the text To visualize these results we recommend that you use an Episodes graph see below It is possible to define the construction level of the Bundles using References fields References or Scenarios as parameters by changing the construction base for the Relations see Analysis options below Using Reference fields instead of Heferences generally results in reducing the number of Episodes detected inside the text in that case the software uses a smaller amount of the generic concepts that have a high occurrence frequency in the text which results in grouping together some utterances and reducing the accuracy of the analysis www semantic knowledge com 18 Tropes Reference Manual Analysis options Use the Tools Analysis option command ptions Conversions Class detection threshold Number of words 3 Pertinence factor 15 El Use ontologies on all words categories Build relations on C Reference fields 1 Reference fields 2 References C Scenario Quantity of characteristic parts of text With this dialog you can both act on the analysis engine of the software and change some display options The Class detection threshold enables you to define the significance level of the Equivalent classes When this threshold is based on a minimum number of words all the Equivalent classes whose occurrence frequency is below this threshold will be ignored i e th
7. ca pda 34 Connecting an Equivalent class to a Semantic Group eee nenea ae nens 36 Applying the Scenario to the text eee nene e nenea ee nenea sns 38 The methodology of Scenario design eese nenea ee nenea aaa nana 39 Scenario management seneca arte too i ta aa a a at E Rino a i a pa atat to rae a li a tul 41 Terminology extracties ase a aaae aa naai E a aiee aigis 42 CHAPTER 3 Borders Mem 45 Corpus segmentation ae caca at zu cate e ta ai taia tt ll ER ut ta i uta la ia aden ia la i uta li ta le i ia i i ta la 46 Creating Borders scai a a a aia 47 Borders files A A A E deine c t 48 CHAPTER 4 Introduction to text analysis eee nnne nnn nnne nnn nnns 49 How Tropes operates ci boot edes sect obra e ees aco ee Sar dala ada doe sax ure ande ae Rd EE x sioe deua br aa deasa atata 50 Propositional hashing scrret caet da iret da d ee sette eu eed eod bod une ed sa cazat Ree catia 51 www semantic knowledge com 2 Tropes Reference Manual Ambiguity SOIVING c eee eee e nenea e nenea ee nenea EEEa Ea EEEE iEn sas 51 Word categorie S mi Qo petala E ata a cada 00 aaa ip ERRORI ca aa dl 51 Statistical probabilistic and cognitive analyses mmee nene nenea nnns 54 Equivalent classes and Relations between equivalents eese 55 Reflections on the size of the texts cena aaa aaa aaa aaa aaa aaa 56 Analysis of heterogeneous utterances open questions dispatches enum
8. developed by UEFISCDI All rights reserved The dictionaries for Romanian version were developed by Dan Caragea for UEFISCDI Romania All rights reserved http www semantic knowledge com http www forhe ro 4 The name Tropes and the name of the authors must not be used to endorse or promote products derived from this software without prior written permission 5 Products derived from this software may not be called Tropes nor may Tropes appear in their names without prior written permission of the authors THIS SOFTWARE IS PROVIDED AS IS AND ANY EXPRESS OR IMPLIED WARRANTIES INCLUDING BUT NOT LIMITED TO THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED IN NO EVENT SHALL THE AUTHORS BE LIABLE FOR ANY DIRECT INDIRECT INCIDENTAL SPECIAL EXEMPLARY OR CONSEQUENTIAL DAMAGES INCLUDING BUT NOT LIMITED TO PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES LOSS OF USE DATA OR PROFITS OR BUSINESS INTERRUPTION HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY WHETHER IN CONTRACT STRICT LIABILITY OR TORT INCLUDING NEGLIGENCE OR OTHERWISE ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE The information contained in this manual may undergo alteration without notice Tropes Adobe Microsoft Windows Excel Word and Apple are registered trademarks To complement this manual consult the Tropes users guides on our website http www se
9. e eee eee e anna nnns nnne 15 Note on Equivalent ClaSSe S cccsccccccccessesesssceeceecessesseaeseecesceeseaeaeeeseceseesesasaeeeesesseesaaeaeeeeseesses 15 Which word categories are frequently used eee nene eee eee anna eee eee aa ea nana 16 Displaying all word categories ete ae Dadaca atac data 16 Lists ot verbs and ad je cts wiii alea anca a agata d pla idea te ace pntat las 17 Episodes and Bundles Iden ettet did Duda Een 18 Analysis A sd ne SE 19 Printing the results d rien eere EE Ee ie VERRE rx ERREUR 21 Equivalent classes and Relations graphs esses eene nnne nennen nn 22 Bundles and Episodes graphs esses eene nennen nnne nnnnnnnnnnnnnr n nass enne 26 General operation of graphs cccececssssececececeesesseaeeecececesseeasecececssessesaeaeeeeeeusessessaaeeeeeeeseesenaeas 27 Copying the graph coc oe pae riii ED e eie bata Duta 0 tene awe 28 Copying the selected text cccccccccccssssssssececeeecessesseaeeececscesseseaseeececseeeseaeaeeeeeeesseseaasaeeeeseesseseaees 28 Graph properties siib ame ivi mia a dt ii erre E aa 28 Changing the Colors is sei T E H 28 Finding AMO Cl secre cosas EE TE 30 RepOFt Writere zecea poze ceas erae iia 31 CHAPTER 2 Semantic Scenarios Ontologies cane nenea nenea nnns 32 INERO ELICEI O fise pios A 33 Creating semantic Scenarios et aa pa t at pa a i i a pa tat ta pa a le a
10. in the Scenario tool enable you without quitting this dialog to take into account the modifications to the Scenario save them and update the display Most of the navigation functions in the Scenario tool are similar to those of Windows Explorer For example to rename a semantic group just select it for a few seconds www semantic knowledge com 35 Tropes Reference Manual Connecting an Equivalent class to a Semantic Group When a Semantic Group refers to an Equivalent class the Scenario tool displays the corresponding line and between parentheses a note containing a star when the item includes a Reference a number 1 or 2 when the item includes a Reference field 1 or 2 a letter V when the item includes a verb lemma a letter A when the item includes an adjective or its lemma In the example below the equivalent class ploaie which is one of the References has been grouped together with the verb ploua and the adjective ploios amp q ploaie Q ap de ploaie q avers q burnit Q curcubeu a poak ploaie ploios A ploua V ploaie moc neasc ploicic precipita ii strop de ploaie EEE n T F amp 4 am am Semantic groups can be designated Visible or Invisible If the box is not checked group invisible none of the words or equivalent classes under the invisible group will be displayed in the results Th
11. neam cunoscut neam m rturisit c i lui i mie ni se p ruse a mai fi Y Relations stat si alt dat impreun ntr o inc pere la fel if Frequent word categories cum cunosteam pe domnisoara v nz toare dec t dupa plecarea lui s intru Y All word categories 3 PA s mi infloresc cheutoarea s r m n asa cum l am cunoscut sem n nd at t de mult cu acei frumosi lorzi Ej Adjectives Y Substantives z I T 0012 crede 0004 cunoaste 0011 da 0003 destepta c l am cunoscut in fiin am ars scrisoarea in a c rei pecete z mbea sfinxul impresurat de zicerea You can add directly these verbs and adjectives in the Scenario Tool These verbs and adjectives can be useful to complete certain analyses in particular if you analyze a series of very short messages where the least information must be got back to define and to test your own qualitative classifications or to make linguistic studies To print these results use the menu File Print and mark options Verbs or Adjectives www semantic knowledge com 17 Tropes Reference Manual Episodes and Bundles Click on the nn Episode s Detected line of the Text Style in the Result frame or use the Show Episodes command This function enables you to study the chronology of a discourse It is based on two notions Bundles and Episodes a Bundle groups together word occurrences belonging to an Equivalent class or to a
12. the text will remain visible To disable all Borders use the Include all button To exclude all the text taken into account by the Borders use the Exclude all button This function enables you for instance to check whether or not the whole text is correctly delimited Once you have finished use the Apply button to restart the analysis of the text This time the analysis will ignore all the parts of the text you have chosen to remove when using Borders for the first time the software will ask you to give a file name in order to save them When the Show Borders in the text option is checked Tropes will count all Borders as words of the text and display them Otherwise if this option is not checked Tropes will not display the related codes which will not be counted as words Note if your Borders are compounds unrecognized by the software you must link together the words forming these compounds with the underline character for example DI Negru www semantic knowledge com 47 Tropes Reference Manual Borders files Use the File menu to create a new empty Borders file open an already existing Borders file save the Borders file under another name Borders are automatically saved when using the File Save menu or pressing the Apply button To quit this tool without saving your modifications click on Cancel www semantic knowledge com 48 Tropes Reference Manual T ropes CHAPT
13. uncia www semantic knowledge com 55 Tropes Reference Manual Reflections on the size of the texts Most of the analyses made by Tropes being statistical the software is sensitive to the amount of text to be processed If your corpus consists of files containing very short texts under one page the results will probably not be significant and the software may have some difficulty in resolving semantic ambiguities there will not be enough words to clarify the implicit concepts If you work on a reasonable number of short texts we recommend that you put them together in a single file If you work on a great number of short texts put them in several files where you can group them in chronological order for instance Otherwise if your corpus consists of files containing very long texts over 100 pages and or composed of utterances referring to completely different contexts the pertinence of the results may be affected the discourses get mixed up When working on rather substantial corpora try to divide them as much as possible into files that do not exceed a few hundred pages You can use a semantic Scenario to merge the results obtained by the analysis of several files A few symptoms indicate that the corpus you are analyzing is too substantial Ittakes more than one minute for Tropes to process the text the Equivalent classes are hardly usable they often contain words of different meanings Tropes has no
14. ER 4 Introduction to text analysis www semantic knowledge com 49 Tropes Reference Manual How Tropes operates To process a text Tropes operates in 6 stages 1 sentence and proposition hashing 2 ambiguity solving regarding the words of the text 3 identification of Equivalent classes 4 statistics detection of Bundles and Episodes 5 detection of the Most Characteristic Parts of text 6 layout and display of the result Words are grouped together in several main Word categories Among these six are of interest to us 1 verbs 2 connectors conjunctions conjunctive phrases 3 modalities adverbs or adverbial phrases 4 qualifying adjectives 5 personal pronouns 6 substantives and proper nouns To achieve an analysis the software carries out a complex processing aiming at assigning all the significant words to the above categories analyzing their distribution into subcategories Word categories Equivalent classes examining their occurrence order both within the propositions Relations Actants and Acted and throughout the text Distribution graph Bundles Episodes Most Characteristic Parts of text www semantic knowledge com 50 Tropes Reference Manual Propositional hashing To simplify the analysis Tropes divides the text into propositions simple sentences This first stage is based on a scrutiny of the punctuation and on complex syntax analysis functions which will n
15. Localize options at the bottom right in the dialog box The terms extracted are preceded by a color code showing which are the most frequent terms or expressions dark frequent light infrequent The extractor is run from the Tools menu of Tropes when you have analyzed a text or preferably several texts on the basis of which you want to build a classification Results Options Explain _ raze gt raze 2 Restore 4 remember gt remember 5 L risip gt risip 2 C ruysdael gt ruysdael 2 Exit O safire gt sapte safire 2 safire gt safire 4 J safire gt safire de ceylon 4 Help _ scrisoare gt scrisoare 2 _ seama gt seama 2 Add Y seam gt seam 3 Q sear gt sear 2 Scenario gt gt 5 seara gt seara 6 _ _ sf r it gt sf r it 2 C sfinxul gt sfinxul 2 dl y e Insert Each term or expression extracted is displayed on a separate line with its membership group It is preceded by a colored square showing its frequency of occurrence www semantic knowledge com 42 Tropes Reference Manual To enrich your classification use the Scenario tool and select the terms that interest you in the terminology extractor doamna gt doamna_ionescu 16 Add F doamna gt doamna martin 11 A E doamn oamn _martin 2 Scenario gt gt FI doamna gt doamna scarlat 6 L doamn gt noua_doamn 2 doamn
16. Tropes Reference Manual Tropes Version 8 1 Reference Manual Software developed by Pierre Molette and Agn s Landr on the basis of the work of Rodolphe Ghiglione The Romanian dictionaries were developed by Dan Caragea for UEFISCDI Romania This version of Tropes software is distributed by Semantic Knowledge www semantic knowledge com All rights reserved and UEFISCDI www forhe ro All rights reserved www semantic knowledge com Tropes Reference Manual Table of contents SA AN 6 CHAPTER 1 Analyzing a text 0 ccsscsssccecessessssseneececeesesssaeensececeesesesaaenseeeceesesssaeanseceeeesessaeanes 7 Saving a document in text format eee eee eee eee eee nenea nenea s tasa sss cnn 8 Starting a text anal isc etes a ost ee cese za veneno a heit anala regu aa al 23 3 eser Brel 8 Examining a text sic der tor rin epe e ava aaa ER aaa HERE VR toaca FERE 030 aia aug uda CREEK RE alele dd 9 Displaying the context iidem tco pe etes deest ede ed dades 10 Wihatis the text Style ss cai rere eee da Ca at utes go eon deae Pda a 11 Most Characteristic Parts of text ceea esee eee eene aaa aaa aaa aaa aaa aaa 12 Reference A 13 References what is the text about ceea eee nea aaa aaa aaa ae aaa ea 13 Act nts and Acted saca pian amo p at alia a Pa ada at t la 3 ati al dalta a a al ala 14 Which elements are frequently connected eee
17. a de fiin e omene ti O ve nicie fi nt lnit tot mai lesne i ar fi sc pat lui o dest inuire dec t mie o intrebare intu nfloresc cheutoarea ca s aflu unde le trimesese i pun nd astfel m na pe fir fiavut un scop st ruin a inc p t nat cu care isi perdeluia scurtul lui trecut i viata de toate zilele se putea prea bine risipeasc orice umbr de neincredere de b nuial Totu i numi sc pase din vedere De la acea scrisoare sir Aubrey n a mai dat semn de viata Nu era de mirare Trecea o femeie nalt cu un bogat p r ro u sub o p l rie mare cu pene o femeie slab i osoas f r solduri i f r s ni ntr o rochie str mt de fluturi negri cu n rile pline de cunoscuta mireasma mireasma de garoaf rosie am dat s o urm resc Era o noapte de catifea i de plumb in care adierea molatec a unui v nt fierbinte cerca in zadar s SI p cred ar tarea ce trecuse pe l ng era o femeie acum mi se p rea Y al A a ee ee ar Trebuie simti si dumneata sl bit de z duf urm el Ai s mi faci pl cerea poate mai mult de un sfert de ceas oricum ins mai putin de o jum tate Cum asteptarea ca toate neajunsurile pare mai grea la inceput am mai luat o pe cheu in sus gt Summarize the Most Characteristic Parts of this text The contraction of the text reveals the Most Characteristic Parts of text These are propositions introducing main themes or characters expre
18. assc tiva b tr ni i Reference fields 2 3 copaci frunzosi si sumbri L Y References A T en B Scenario c afl nelipsit un t n r care acolo mai ales ar fi atras privirile oricui Y Relations pecu DERE A CUTTS GNI OCULI OTOL Y Frequent word categories X care copia dupa Mignard pe Maria Mancini si avea o asa izbitoare asem nare cu modelul V F in deplin frumuse e p sea singur in via nep s tor cu fruntea sus L am crezut din capul locului una din acele f pturi excep ionale str ine de omenire Poen sapis Al turi de mine pe singura lavit din primitoarea c mar singuratic ziua t n rul cu chip de portret vechi EQ ME sorbea pe indelete b uturile cele mai dulci i mai parfumate asemenea unor nestimate topite at t toare de vis ri LL Some notions of doubt has been detected Acolo parc nu mai eram str ini unul de altul ceea ce e nostim mai t rziu una e floarea de c mp alta floarea de gr din Acum fie c trebuiser veacuri ca 18 Episode s detected Numele lui normand pana ast zi nu tiu dac astfel se cheam intr adevar numi era str in c nd la una c nd la cealalt sclipeau apte inele gemene toate sapte safire de Ceylon Cu br tara i cu parfumul acea de neuitat mireasm de garoaf ro ie inelele erau singurele lucruri P rea chiar s fi avut mai multe leg turi cu duhurile dec t cu cei vii deoarece n povestirile sale nu venea niciodat vorb
19. bers percentages etc Only alphabet letters and punctuation characters will be used during the analysis If you want a series of words to be considered as a single word link these words together with the underline character for instance seful statului To get better results use punctuation and respect the typographical conventions in use in Romanian The spellchecker of some word processors can enable you to ensure that these conventions are fully respected Starting a text analysis To analyze a text start Tropes use the File Open command select a file and click on OK You can open several files simultaneously by using the Ctrl and Shift keys of your keyboard when opening files It is also possible to use the drag amp drop function of Windows Explorer grab a text with the mouse and drop it on the main window of Tropes After starting to run the analysis you can also use the File tab to add or delete documents display them open them sort them etc www semantic knowledge com 8 Tropes Reference Manual Examining a text As an introduction to the software we suggest the analysis of the example file Remember txt Once a text is opened and as soon as the analysis is over its content is displayed File Edit Show Tools Help ss ES Ej Reference fields 1 Ej Reference fields 2 Y References Y Scenario Y Relations Y Frequent word categories da PF J Style rather argu
20. by the ochi goliciune etc classes On the right are many successors to albastru lic rire amp floare orhidee br ar etc The figures shown on the graph give the number of Relations co occurrence frequency existing between the various Equivalent classes You can follow the Relations shown on the graph by clicking directly on the classes you wish to study This very powerful function enables you to move through a text while viewing its micro worlds and analyzing the connections between its various actors When you use the Relations the graph reveals two central classes In this example we can see that there are only two Relation leading from the albastru class to the sear class whereas there is one Relations leading from the sear class to the umbr and vechime classes yw semantic knowledge com 23 Tropes Reference Manual The graph of the actors represents the concentration of relations between the main actors actants acted in the whole of the text It can be used to make a visual comparison of the weight of the Relations between the principal references or between the groups in the Scenario The references are displayed along two axes the X axis horizontal shows the actant acted ratio from left to right the Y axis vertical shows the concentration of relations for each reference strong at the top of the graph weak at the bott
21. cenario the software will no longer identify stelu a as an astru on the other hand the Doamna Steluta compound will appear in the References The lower level equivalents have priority over the higher level equivalents i e if you create a semantic group containing a single word this word will not be counted in another Semantic Group including an Equivalent class that contains this same word For example if you assign the word ploicic to the ploaie Group this word will be excluded from the ploaie Reference field even if this field is assigned to another Semantic Group If you wish to create a Scenario that is relevant to a series of texts we recommend that you collect inside a single file a sample of texts representative of what you intend to analyze and then build your Scenario from this sample www semantic knowledge com 37 Tropes Reference Manual Applying the Scenario to the text Once you have created the Semantic groups of your Scenario and as soon as it has been saved you can use the Scenario command in the Tropes main window File Edit Show Tools Help S Sea E ala Results Explain Tex Files Ej Text E MATEIU CARAGIALE REMEMBER ortografie actualizat Ceci est un fait divers atroce Les M moires du Bal Mabille Sunt vise ce parca le am trait c ndva si undeva precum sunt lucruri vietuite despre care ne intreb m dac n au fost vis La asta m g ndeam deun zi s
22. dverbs of doubt have been detected To obtain an explanation of the displayed Style or of the Setting click on the line concerned a color display in the main window will show you all the words whose categories have been taken into account to make the diagnosis The study of the Text Style and of the Setting of a text written by you directly or indirectly is especially interesting when the software makes a diagnosis that proves contrary to your purposes For instance you will presumably want to find out why the Style has been detected as argumentative when it was not intended to be Likewise you will probably try to avoid as much as possible the Settings involving with I if your text is written on behalf of a group or to rule out all notions of doubt from a financial offer a contract etc Important note since the analyses are carried out on a statistical basis the studied texts must be of sufficient length for the results to be significant www semantic knowledge com 11 Tropes Reference Manual Most Characteristic Parts of text To display the Most Characteristic Parts of text click on the nn Most Characteristic Parts of text line of the Text Style Results Explain Extract Files B intorceam la Berlin acas ns n to irea mea se f cea cu anevoint cer nd ingrijiri mari a i Reference fields 1 3 admir col ul cel mai frumos al pietei un petec de p dure r mas neatins in plin or
23. e gt doamne 6 C doamne gt doamne_dumnezeule 2 Y doamnei gt doamnei 3 C Add W doamnei gt doamnei ionescu 2 LI dobitoc gt dobitoc 2 domnul gt domnul 90 IV Subclassify domnul gt domnul_ionescu 36 domnul gt domnul martin 11 domnul gt domnul neacsu 16 Insert Localize domnul gt domnul scarlat 26 J domnului gt domnului 3 W domnului gt domnului neacsu 2 IV Scenario Li don gt don 2 Li don gt don_quijote 2 V Text We will then check the Insert box and click on the Scenario button on the right to transfer them automatically into the Scenario The software will automatically create all the entries and corresponding group labels in the Scenario tool doamna E Doamna ionescu Bill doamna_ionescu Bil doamnei ionescu Doamna martin Bl doamna martin i af ioa marin Doamna scarlat il domnul ionescu Domnul martin Bil domnul martin Domnul neacsu ill domnul_neacsu domnului neacsu lt Domnul scarlat E dnmnul scarlat All you have to do then is save your Scenario Save command in the File menu of the Scenario tool to see the result in the text analyzed When you select a term and provided the Scenario tool is open the software will try automatically to position the Scenario on the closest semantic category This behavior can be inhibited by remo
24. e si grave fiindc nu cred s t i Answer to the questions What is the text style How is it situated L 18 6387 Substantive The main analysis results are displayed inside the frames on the left of the screen while the text and the graphs are shown on the right This window responds according to the text When the mouse cursor is placed on a word of the text the message bar at the bottom of the screen shows the category of this word in the above example this word is a substantive In this case the nn ww indicator on the left of the message bar indicates the occurrence number of the word pointed at by the mouse When the display applies to a subset of the text only the categories concerned appear in color To display the whole text use the Show All the text command or the All button of the tool bar www semantic knowledge com 9 Tropes Reference Manual Displaying the context To display the context of a proposition click on the icons on the left margin of the text extracts or point at any word then press the right button of the mouse and select the Context command in the context menu The display of the context is similar to that of the main window syntactic coloring of words etc Extract Files File Edit Help sm 0 eme C Users impactaxis Desktop Remember txt Use the toolbar or the menu to access these files This tool proves useful
25. eara c nd r v ind printre h rtiile mele ca s v d ce se mai poate g si de arsith rtile incurc stam dat T peste o scrisoare care mi a desteptat amintirea unei int mpl ri ciudate asa de ciudat c de n ar fi dec t sapte ani de cand s a petrecut m as simti cuprins de indoial as crede c intr adev r am visat numai sau c am citit 0 ori auzit o demult Era in 1907 Fusesem greu bolnav in Bucuresti si m E p is g 3 m jj References Y Frequent word categories Y WM Acat N Acted q 0004 anotimp r3 0001 prim var ntorceam la Berlin acas ns n to irea mea se f cea cu anevoint cer nd ie ngrijiri mari La plecare doctorul m a sf tuit s m feresc p n si de cele 4 0002 calendar mai u oare zguduiri suflete ti Bietul doctor Am dat din umeri z mbind i i Bit am spus s fie pe pace Dup un surghiun de doi ani revedeam Berlinul Am Plon par gu de Berlin mare sl biciune nici imprejur ri foarte triste nu m au impiedicat s l L 0004 cip rev d cu pl cere L am reg sit cum il l sasem tot numai flori A a frumos chiar ca n acel inceput de iunie numi p ruse totu i niciodat Ca s l v ntur ns i s l colind ca odinioar nu mai mergea Oboseam repede i oboseala 4 m D HS Am e putea inlesni reivirea bolii M am resemnat dar c t va vreme a sta pe acas jertf de care m desp gubea in parte f
26. enables you to display a histogram showing the distribution of an Equivalent class of a Relation i e between two Equivalent classes or of a Word category sear x Deed Un MUN el Graph Explain AU In the above example we can see that the sear Equivalent class appears rather at the end right side than at the beginning left side of the text This graph is obtained by splitting the text into several sectors containing the same number of words and by calculating the occurrence frequency of the selected Equivalent class within each sector The histogram bars present each sector in chronological order from the left beginning of the text to the right end of the text The dotted line indicates the average size of the histogram bars When clicking on a given bar the display will automatically position itself on the propositions appearing from this point of the text onwards To return to the standard display make a second click on the same bar When pointing at a given part of the histogram the message line displays the number of words contained by the selected sector as well as its place beginning and end of the sector calculated in number of words from the beginning of text The number of histogram bars and the sum of words contained in each bar are automatically determined by the software according to the total of words in the text and to the size of the main window When the distribution graph c
27. ence fields 2 Iv References Scenario Relations Adjectives To print results check the related boxes then press Print otherwise press Exit Printing the report of the Equivalent classes and of the Scenarios discloses a utilization rate expressed in a percentage that corresponds to the number of words contained in each class divided by the total number of words contained in the text Printing the report of the Relations discloses an additional item of information not displayed in the Relations of the results dialog the connection rate This rate is obtained by dividing the number of observed Helations by the highest number of possible Relations A connection rate of 100 shows that one of the two terms of the Relation is always presented with the other A connection rate that is close to zero shows that the two terms are almost never presented together In the printing options various buttons enable you to change the configuration of the printer and to select the font you wish to use for the printing The Color box enables you to print in color if you have a color printer www semantic knowledge com 21 Tropes Reference Manual Equivalent classes and Relations graphs For the graph display you can choose between the following modes Area Star Distribution or Episodes Use the context menu that appears when clicking on an object of the graph with the right button of the mouse The first two graph
28. erations etc 57 Analysis of discourses and conversations cena nenea e nenea ee nenea eee nnn 58 Literary A e DUE BUDE ELE 58 Comparing tWO texts ui oen nia e a iate e nu E 59 CHAPTER 5 Appendices ss cca ea cca aa c aa 60 Files conversion de vaii 61 www semantic knowledge com 3 Tropes Reference Manual Important notice e This first Romanian version is a prototype It only accepts Romanian texts properly written with diacritics e The conversion of PDF documents may require the installation of an Adobe IFilter component on your system You can download the latest version of Ifilter on Adobe s site Romanian dictionaries and software grammar are in continuous evolution Please download always the latest versions from our sites e For specific linguistic topics specialized dictionaries etc please contact us Typographical conventions The Windows commands accessible by the menus or the dialog boxes and the text referring to the buttons are written in italics and in square brackets For example File Open refers to the Open command of the File menu Cancel refers to the Cancel button of a Windows dialog box The specific vocabulary of the software is written in italics for example Equivalent classes Notes Though it is possible to install this software in a different folder than the default folder we will consider in this manual that t
29. ere the results are expressed in number of word occurrences and in Zoom where the results are expressed in number of documents Note that modifying the default type of graph in Microsoft Excel enables you to have at your disposal numerous options to control the layout of the report www semantic knowledge com 31 Tropes Reference Manual T ropes CHAPTER 2 Semantic Scenarios Ontologies www semantic knowledge com 32 Tropes Reference Manual Introduction Scenarios are designed to enrich and filter Equivalent classes according to an analysis strategy With them you can define your own personalized classifications ontologies modify or restructure the software s dictionaries replace a thesaurus and personalize your information retrieval functions define an analysis grid for automatic generation of an analysis report see Report writer in this manual or statistics when indexing your documents see Using a Scenario in the Zoom manual Why is it necessary to use Scenarios when it is tempting simply to make modifications directly to the Tropes dictionaries Because you need to use classifications adapted to your analysis objectives and these depend on what you want to do with your texts For example it is perfectly correct to classify pepene ro u castravete pepene galben dovlecel in the curcubitacee family if you want to conduct botanical analyses If it is the domain of food
30. es results window using the Show Scenario menu in the main window if necessary 9 examine the result obtained by going down the list of groups in the Scenario 10 correct misclassifications by adding them directly in the Scenario tool for example if the White House is classed among colors you must move it into another group 11 remove the narrative branches which are not useful for your analysis from your Scenario for example the days of the week are generally of little interest when analyzing newspaper articles 12 interpret the result and go back to step 7 if necessary 13 when you have checked everything your analysis is done www semantic knowledge com 39 Tropes Reference Manual As the References are sorted in decreasing order of frequency you can be sure that you have classified the main references in your texts when you employ this method even if you do not incorporate all the semantic classes in the Scenario For example if you halt the construction of the Scenario when the References reach a frequency of two occurrences i e generally not very relevant you cannot be accused of making a hash of the analysis You will simply have focused on the essentials by halting the analysis at a particular moment www semantic knowledge com 40 Tropes Reference Manual Scenario management The File menu of the Scenario tool enables you to create a new Scenario open an already existing Scenar
31. ether the main substantives of the text analyzed into Equivalent classes The software detects the Heference fields by using two different representation levels of the context Reference fields 1 and 2 To view the content of a field select this field and all the words that compose it will then be displayed in blue in the main window File Edit Show Tools e Se Ge Sy e m B alal Results Explain Help Extract Files Y Text style m Ej Am dat din umeri z mbind si i am spus s fie pe pace E W Reference fields 1 3 cu ochii pe jum tate nchi i cum unduiau curcubeie in pulberea fluid a f nt nii E if Reference fields 2 E din larga piat gr din pros Lina boare a asfintitului leg na ciucuri purpurii ai trandafirilor ag tati pe terasa Ej Relations SSE din fata Ej Frequent word categories X mpodobindu l propriul ei chip Tot astfel sem na t n rul cu unii din acei lorzi 3 7 Actant 7 Acted ale c ror priviri m ini i sur suri Van Dyck i dup el Van der Fae le au h r zit nemuririi E by in deplin frumusete p sea singur in viat nep s tor cu fruntea sus L am TM crezut din capul locului una din acele f pturi excep ionale str ine de omenire Bi 0061 ii Si ii m ee Al turi de mine pe singura lavit din primitoarea c mar singuratic ziua t n rul Bi 0058 om Bil 0055 plante E cu chip de portret vechi sorbea pe indelete b ut
32. ey will not be displayed When this threshold is based on a pertinence factor all the classes whose pertinence factor is below this threshold will be ignored The pertinence factor is calculated in ten thousands of number of words For instance a pertinence factor of 10 corresponds to a minimum occurrence frequency of 3 words for a 3 000 word text You can change the Class detection threshold if you want the software to process only the most frequent classes or conversely to take into account the less frequent classes Important note the higher you raise the thresholds the more information you lose And vice versa when you lower the thresholds you increase the amount of information taken into account by the Equivalent classes The analysis options dialog also enables you to change the Construction base for the Relations using the Build Relations on box i e the Equivalent classes level needed to build display and print Relations Episodes and Bundles www semantic knowledge com 19 Tropes Reference Manual For example if you use Scenarios it is possible to build the Relations from the content of the current Scenario see Chapter 2 Semantic Scenarios It is also possible to modify the contraction rate by using the cursor which enables you to adjust the Quantity of characteristic parts of text to be displayed Since it is uncertain whether the software will or will not be able to detect with the greatest acc
33. finding two Equivalent classes several times in the same text in the same order is indeed unlikely to happen When it does it means that these two c asses are strongly connected and this reveals the notions emphasized by the author of the text but not necessarily what he intended to put into the text The display of the Heference fields of the Heferences and of their Relations brings you to the heart of the discourse all the actors objects things and concepts presented in the text will appear before you in decreasing order of importance Note on Equivalent classes In this manual the term Equivalent classes refers equally to Reference fields and to References For further details about Equivalent classes consult Chapter 4 Introduction to text analysis Note about the dictionaries Since it is neither possible nor relevant to classify all of the English substantives names forenames and proper nouns the software automatically generates Equivalent classes for all the words that are not referenced in the dictionary Such generated classes are visible only in the References The generated classes Other for instance are preceded by a blue square whereas the Equivalent classes detected by the software are preceded by a red square To group generated classes together with Equivalent classes and so create your own personal classification you have to use a semantic Scenario see chapter 2 www semantic knowledge co
34. gning your Scenario For example you may use an existing Scenario such as those supplied with the software supplement it and refine it according to your working hypotheses You can also start off with an empty Scenario which you will build up gradually on the basis of a text We suggest that you adopt the following methodology which gives good results quickly 1 open the Scenario tool Tools Scenario menu in the main window and load one of the existing Scenarios File Open menu in the Scenario tool which you then save under another name File Save as menu in the Scenario tool 2 analyze a collection of documents representative of the subject that you want to deal with 3 display the References 4 supplement the Scenario by adding all the words that are not classified that is to say are not checked in the list of References and which are relevant to the subject of your analysis 5 display the Relations or the expressions proposed by the terminology extractor and use them to classify the relevant compounds in the Scenario for example if you are studying the Mateiu Caragiale files in the example texts you should group Aubrey together with Vere to carry out a correct analysis of the text 6 you may wish to study the lists of verbs and adjectives some of which can strengthen the Scenario 7 apply your Scenario to the text File Save menu in the Scenario tool 8 move on to the Scenario in the Trop
35. he home folder of Tropes is named tropes and is located on the hard drive c i e c Program files Tropes Tropes Most of the drawings used in this documentation have been captured in Windows XP Although the aspect of windows and dialog boxes may slightly vary from that of other versions of Windows Legal notice Please read TROPES LICENSE AGREEMENT before using this software Tropes software was developed by Pierre Molette and Agn s Landr on the basis of the work of Rodolphe Ghiglione All rights reserved The dictionaries for Romanian version were developed by Dan Caragea for UEFISCDI Romania All rights reserved Redistribution and use in binary forms are permitted provided that the following conditions are met 1 Tropes software must be distributed for free Reselling this software or its components is strictly forbidden 2 Redistributions of the software must reproduce the above copyright notice this list of conditions and the following disclaimer in the documentation and or other materials provided with the distribution www semantic knowledge com 4 Tropes Reference Manual 3 Redistributions of any form whatsoever and all advertising materials mentioning features or use of this software or its components must display the following acknowledgment Tropes software was developed by Pierre Molette and Agn s Landr on the basis of the work of Rodolphe Ghiglione The dictionaries for Romanian version were
36. his the software can try extract the text by binary analysis for problematic or not recognized files The installation Microsoft Word or Office 2007 or the equivalent 32 bits IFilter pack is a prerequisite for DOCX documents Software uses a specific driver Adobe IFilter to extract the relevant text of PDF Portable Document Format files If Adobe Reader installation is not needed it is necessary on the other hand to install a PDF IFilter driver to benefit from this file format The usage of external character recognition software OCR may be necessary for some files those that come from a digitalization by scanner The software interprets RTF Rich Text File formats containing characters in ANSI SO 8859 1 Apple Macintosh or ASCII IBM coded on 7 or 8 bits Unicode format is not accepted Because disparities exist between RTF standards parasite characters can appear in certain files The software discards the tags of SGML Standard Generalized Markup Language ISO 8879 and converts some HTML specific variables or entities e g some characters or diacritics It does not interpret the DTD UTF 8 format UCS transformation 8 ISO 10646 RFC 2279 is converted in ANSI S0 8859 x The other Unicode formats Universal Character Set ISO 10646 are not accepted No conversion is made on this file format considered in ANSI ISO 8859 1 a k a ISO LATIN1 or ANSI Windows or in Unicode UTF 8 if a Byte Order Mark is in the file header
37. his dialog enables you to define the parameters of the graphs You can change the Type of graph to be displayed Star Area Distribution Episodes modify the Maximum number of objects in the Area graph show the Bundles on all word categories including Connectors Modalities etc or if unchecked on Equivalent classes only which makes it easier to read when studying a very long text All modifications become immediately effective If you wish to store them permanently click on OK otherwise click on Cancel Changing the colors Use the Edit Colors command of the main menu or the Colors command of the menu that appears when clicking on the main window with the right button of the mouse This dialog enables you to change the colors of each Word category that is displayed of the borders framing the classes displayed before and after the central class of the graph of the background of the areas drawn on the graph www semantic knowledge com 28 Tropes Reference Manual and to choose between Selective only the displayed elements are colored or Syntactic all word categories are colored coloring It is also possible to choose the texture of the areas which can be either opaque full or striped transparent The Restore button cancels all color changes made after the initial installation of the software www semantic knowledge com 29 Tropes Reference Manual Finding a w
38. ialized with the other Scenarios or those available on request www semantic knowledge com 33 Tropes Reference Manual Creating semantic Scenarios To create a Scenario use the Scenario command in the Tools menu File Edit Tree Help Sal S eli allel xi Seach tunz Y ciuperci familii si specii de plante fitopatologie floare flor fotosinteza v 2 a 4 4 4 4 4 he he he he H A psu Botanica Iv Visible Group Tropes is supplied with a number of default Scenarios rich in classifications which can serve as a Starting point for the rapid creation of a new classification plan We advise you to be careful to keep the Scenarios supplied with the software and to save them under a new name if you want to modify them A Scenario consists of a number of Semantic Groups i e groups of words and or Equivalent classes which can be arranged in a hierarchy of nine ranks Most combinations can be made by means of the mouse either in the Scenario tool or interactively with Tropes main window Just create a group and put something into it When viewing a Reference in the Result frame you can add it directly to the Scenario by dragging it with the mouse and dropping it on the Scenario tool In Tropes Version 8 and later you can also add the verb and adjectives lemmas or their lemmas in languages other than Romanian directly in the Scenario It is also possible to grab a word in Tropes Te
39. ing adjectives Do not take these categories into account because they are used only for www semantic knowledge com 52 Tropes Reference Manual ambiguity solving Broadly speaking we can say that time and place connectors and modalities provide the means to locate the action intensity and negation modalities provide the means to dramatize the discourse cause and condition connectors provide the means to construct a chain of reasoning addition connectors provide the means to enumerate facts or characteristics opposition connectors more specifically provide the means to argue to put things into perspective and to set out conflicting standpoints www semantic knowledge com 53 Tropes Reference Manual Statistical probabilistic and cognitive analyses Tropes carries out different sorts of text analyses statistics on the total occurrence frequency of the main Word categories and of their subcategories statistics on the total occurrence frequency of the main Word categories and of their subcategories a probabilistic analysis of the words occurring in Bundles and a geometric analysis of the Bundles delimiting the Episodes a Cognitive Discursive Analysis CDA making it possible to detect the Most Characteristic Parts of text Among other things statistics are used to build the graphs and to lay out the results The Frequent word categories and the Text Style are obtained by comparing
40. io save the current Scenario under another name print the definition of the Scenario find the folder containing your Scenario files For the creation of a new Scenario New Wizard in the File menu an assistant will help you create it automatically from a text or from an existing Scenario or several Scenarios Welcome to the New Scenario wizard With the Scenario you can build your own classifications How do want to create your Scenario Manually from an empty Scenario Automatically from the current text From existing Scenarios Note to work without Scenario you must create an empty Scenario If you do not want to use an existing Scenario just create a new empty Scenario and build it up However you are strongly recommended not to work without a Scenario Note that the Edit Cancel all changes command enables you to cancel all the changes made since the Scenario was last saved Important 1 The names of files containing Scenarios must have the suffix SCN for example Hemember scn 2 lt is essential to store Scenario files in the Scenario sub folder of the software installation folder c Program files Tropes Tropes scenario or in the folder that you designated when installing the software if you opted for multiple users mode 3 Save the contents of this folder regularly Use the File Folder menu in the Scenario tool to copy your Scenario files www semantic kn
41. is makes it possible to hide a branch temporarily without being forced to delete it The Scenario has been designed to solve ambiguities manually which means that when you add a word to a Semantic group Tropes will cease solving ambiguities For example if you add the word p r to the Botanic group in the Scenario concept you inhibit the ambiguity solving mechanism p r will then always be associated with Botanic whatever the text under analysis To obtain ambiguity solving use Equivalent classes By virtue of these principles you must avoid placing a semantic class or a word in two different groups if you do this the anomaly will be pointed out when you save the Scenario and the second entry will not be taken into account Notes If you enter a noun you must add it from References or Substantives In this case you add all its declination in Romanian In contrast if you will add an www semantic knowledge com 36 Tropes Reference Manual unrecognized noun you must decline it if you will find all its forms UUUT jarig 7 0001 pre E Add in the Scenario 7 0001 bal Es Insert in the Scenario mi NANA ies If you enter a compound unrecognized as such initially in a Scenario it will be added to the software s dictionary This means that the words forming this compound will not be taken into account independently any longer in the Equivalent classes For example if you enter Doamna Steluta in the S
42. le format For more information about the files supported see http www apple com http www adobe com http www microsoft com http msdn microsoft com http www unicode org http www utf 8 com http www macromedia com http www w3 org http www w3 org MarkUp http www w3 org MarkUp SGML www semantic knowledge com 62
43. m 15 Tropes Reference Manual Which word categories are frequently used Click on the Frequent word categories line of the Result frame or on the Show Frequent word categories menu This function displays the most significant Word meta categories of the studied text Results Explain Y Scenario Y Relations YY Frequent word categories Extract Files B ce se mai poate g si de arssth rtille incurc stam dat peste o scrisoare care mi a desteptat amintirea unei int mpl ri ciudate asa de ciudat c z de c nd s a petrecut m a sim i cuprins de indoial as crede c ntr adev r k categories a am visat numai El Adjectives sau c am citit o ori auzit o demult Era in 1907 Fusesem greu bolnav in Li Substantives F Bucure ti i p EV m m intorceam la Berlin acas Ins n tosirea mea se f cea cu anevoint cer nd ngrijiri mari Teen Sass PE s m feresc p n si de cele mai u oare zguduiri suflete ti Bietul doctor N Stative 29 2 351 z mbind si i am spus s fie pe pace Dup un surghiun de doi ani revedeam Bl Reflexive 12 4 149 Berlinul Bi Performative 0 0 0 nici mprejur ri foarte triste nu m au impiedicat s l revad cu pl cere E L am reg sit cum il l sasem tot numai flori Asa frumos chiar ca n acel nceput ondition 3 M aa Ea SIE de iunie numi p ruse totu i niciodat Il Cause 44 1 201 Inc M Juan at e es m A W
44. mantic knowledge com and http www forhe ro t 1 edition March 2012 www semantic knowledge com 5 Tropes Reference Manual Introduction What is the content of a text Or to be more precise what are the core elements which must be identified in order to grasp the essential meaning of a text Whether it is a press article a book a speech or any other sequence of language every text contains a few key sentences conveying the ideas that make up its framework its skeletal structure The problem then is to locate this central core of the text that holds the essentials of its meaning This is the crucial first step before any attempt at interpretation can be made We can say that a text consists of various worlds in which different actors do form or say various things in combination with other actors And we can say that these worlds which are invariably propositional in form have different levels of importance in the structure of the text And finally we can say that some of these worlds a very small proportion of them constitute the foundations of the text in that if they were removed the textual construction would collapse and the meaning would be lost Content analysis then applies a set of techniques to a given text to determine the identity of the main actors the relations in which they stand to each other the hierarchy of these relations and how they evolve To sum up content analysi
45. mentative LL Setting dynamic action LL Setting involving with Tr LL Some notions of doubt has been detected C 47 Most Characteristic Parts of text 17 Episode s detected Text Files B MATEIU CARAGIALE REMEMBER ortografie actualizat Ft Ceci est un fait divers atroce Les M moires du Bal Mabille Sunt vise ce parca le am trait c ndva si undeva precum sunt lucruri vietuite despre care ne ntreb m ar o foot is La asta m g ndeam deun zi seara c nd r v ind printre h rtile mele ca__ Substantive poate g si de arssth rtiie incurcd am dat peste 0 scrisoare care mi a desteptat amintirea unei int mpl ri ciudate asa de ciudat c de n ar fi dec t apte ani de c nd s a petrecut m a sim i cuprins de ndoial as crede c ntr adev r am visat numai sau c am citit o ori auzit o demult Era in 1907 Fusesem greu bolnav in Bucuresti si m intorceam la Berlin acas ns n to irea mea se f cea cu anevoint cer nd ingrijri mari La plecare doctorul m a sf tuit s m feresc p n i de cele mai u oare zguduiri suflete ti Bietul doctor Am dat din umeri z mbind i i am spus s fie pe pace Dup un surghiun de doi ani revedeam Berlinul Am de Berlin mare sl biciune nici imprejur ri foarte triste nu m au impiedicat s l rev d cu pl cere L am reg sit cum il l sasem tot numai flori A a frumos chiar ca in acel nceput de iunie numi p ruse totu i niciodat Ca s l v nt
46. n and checkbox at the bottom of this dialog The semantic Groups of the Scenario appear in the Equivalent classes list and are displayed in blue note for this function to work you must first save the Scenario on the studied text www semantic knowledge com 30 Tropes Reference Manual Report writer The report writer gives you the possibility to automatically build reports containing statistical tables and graphs in Microsoft Excel by using the results obtained with the Scenario To use it you must select a branch of the Scenario then use the Tool Report menu Parameters Explain Statistics on r C C All data of the fe The totality of the Scenario Graph Iv Show graph Type By default m Maximum number of graphs e E Help Exit You can make statistical tables on the selected element i e the semantic groups of the same level all the data of the branch that contains the selected element the totality of the Scenario which can be very voluminous You can choose to display graphs for each generated statistical table then choose their type histogram etc and control the maximum number of graphs displayed bearing in mind that a huge number of graphs is sometimes difficult to utilize and that your spreadsheet cannot deal with an unlimited amount of graphs This module requires a recent version of Microsoft Excel and is accessible both in Tropes wh
47. nating conjunctions conjunctive phrases link together various parts of the discourse through concepts of condition dac etc cause fiindc etc www semantic knowledge com 51 Tropes Reference Manual goal cu scopul de etc addition si etc disjunction sau etc opposition dar etc comparison ca etc time cand etc place unde etc Personal pronouns are displayed in gender eu tu el etc and in number ei noi etc Modalities adverbs or adverbial phrases enable the speaker to get involved in what he says or to locate what he says in time and space through concepts of time acum etc place aici etc manner r u etc assertion da etc doubt probabil etc negation nu etc intensity mult etc Adjectives are either objective i e enabling to characterize beings or objects regardless of the speaker s standpoint color adjectives for example subjective i e indicating judgment on something or on somebody thus enabling to express the speaker s standpoint frumos mic nostim etc or numeral i e grouping together numbers in letters or in figures along with ordinal and cardinal adjectives Other word categories include pronouns articles prepositions and non qualify
48. nt neyricos si nu tiu ce as fi in stare de fric These four parts correspond to a conversation between two characters cucoana and narator see the Bubico txt file in the example texts supplied with the software If you wish to automatically separate the discourse of cucoana parts 2 and 4 from that of narator parts 1 and 3 then you have to use Borders www semantic knowledge com 46 Tropes Reference Manual Creating Borders To create a Borders file use the Tools Borders command File Help p narator Add IV inceput naratiune IV p cucoana C A Dee IV sf rsit naratiune Include all Exclude all HE EEE Show borders in the text Borders To create a new entry in the Borders write a word in the upper field then press the Add button This word has to be representative of a sequence of the text analyzed In the example shown above the codes inceput naratiune and sf rsit naratiune have been used to identify the descriptive parts and the introduction of the play while the various speech turns of the characters have been coded by putting the code p after the names of the characters To delete an existing Border select it and press Delete Once you have created your Borders you can choose which parts of the text you wish to ignore by checking the related Borders when a Border is checked then all the following text will be ignored if not the rest of
49. oftware 1 The Scenario has priority then over the other classifications all the non substantives entered as items in the Scenario will be removed from their original categories For example if you enter the item acum in the Scenario the corresponding adverb of place will no longer be displayed in the Modality category in which it will nevertheless be counted 2 The Scenario takes precedence then over the syntactic analysis of the text if an ambiguous word simultaneously used in various grammatical categories appears in a text and if this word is placed in the Scenario then all its various forms will be counted in the Scenario For example if you have entered the word sare in a Scenario later used to analyze a text containing the following sentences Broasca sare n ap and A fost primit cu p ine cu sare then the two occurrences of sare the verb and the common noun will be counted in the Scenario 3 The above observations only apply when you enter words in the Scenario if your Scenario is built from Equivalent classes or verbs adjectives substantives lemmas these will pose no classification problem the Equivalent classes and lemmas have lexical and semantic ambiguity solving www semantic knowledge com 20 Tropes Reference Manual Printing the results Use the File Print command Want do you want to print iv Text Style and categories Reference fields 1 Refer
50. old see Analysis options Thresholds and or by deleting the display of the Word categories see Graph properties General operation of graphs To disable the graph display use the Hide command of the menu that appears when clicking on the graph with the right button of the mouse To display the graph again click on a graph type button on the toolbar To print a graph display it then use the File Print command and check the Graph option To modify the size of the window allotted to the graphs or that of the text use the mouse to move the horizontal split bar at the center of the main window www semantic knowledge com 27 Tropes Reference Manual Copying the graph When a graph is displayed you can use the Edit Copy Graph command to transfer the graph to the Windows clipboard To retrieve this graph and include it in a report for example use the Edit Paste command of your word processor Copying the selected text When the display applies to a subset of the text for example when viewing an Equivalent class you can use the Edit Copy Selected text command to transfer the selected propositions to the Windows clipboard To retrieve these propositions use the Edit Paste command of your word processor Graph properties Use the Edit Graph command of the main menu or the Properties command of the menu that appears when clicking on an object of the graph with the right button of the mouse T
51. om The concentration of relations is calculated for each reference by dividing the total number of relations by the number of different relations The lines show the relations between the reference selected and the other references displayed A dotted line shows an infrequent relation A solid line indicates a frequent relation The example below is taken from the analysis of the Remember txt One of the most has been selected frequent reference sear X TEREE Graph Explain In this example the software has positioned the principal concepts calendar perioad ap etc at the left actants with a high concentration of relations while the secondary concepts are positioned either at bottom left actants with a low concentration of relations or on the right acted Most of the other references are acted on the right The frequency of relations and the number of different relations are indicators of the centre of interest of the text analyzed If the author or authors of the text have associated a reference with many other references it may be deduced that this reference is very important or at any rate more important than others On another level this new graphical representation shows an overall graph not depending on the selected reference alone as is the case with the star and area graphs www semantic knowledge com 24 Tropes Reference Manual The distribution graph
52. oncerns a Relation the histogram gives the accumulated occurrence frequencies of the classes contained in the Relation www semantic knowledge com 25 Tropes Reference Manual Bundles and Episodes graphs The Bundles graph is displayed when viewing an Episode and using a distribution graph see Graph properties below Each Bundle is displayed in the form of a horizontal dotted line indicating its extent length and its place in relation to the beginning of the text As with the distribution graph the chronological order is represented on the horizontal axis from the beginning on the left to the end on the right of the text A Bundle sassussasasusususuan Beginning of text End of text The Bundles are displayed from the top downwards and from left to right according to their occurrence order in the text Once at the bottom of the screen the software makes a zigzag scan in order to display as much information as possible f N N Beginning of text End of text The Episodes appear on the same graph They are displayed from left to right in chronological order and in the form of large dotted frames Episode pl Episode i Episode 1 2 3 Beginning of text End of text y Only the Bundles contained in the selected Episode shown by a hatched frame are displayed in color www semantic knowledge com 26 Tropes Reference Manual When clicking on a Bundle the corresponding propositions are displa
53. ord Use the Edit Search command or the Search command of the context menu that appears when clicking on a word of the text with the right button of the mouse Search Add 4 LEX Type a word sear Connect it to e Itself this word C Asemantic class 3 V sear sear Scenario sear sear sear L ssear timp f I L gt timp Y Fromthetop JV Whole word only Scenario gt gt Insert C Add E E lv Create a group for each added item To use this dialog type a word then press the Enter key or the Search button If the software finds the word sought the propositions containing this word will be displayed in the main window otherwise you will hear a beep Depending on the chosen option the search will be carried out either within the text option Itself or within the Semantic classes or Groups of the Scenario The second case requires that the corresponding Equivalent class exists in the text and incidentally that the last modifications of the Scenario have been applied If the Start from the top box is checked the search will be carried out from the beginning of the text otherwise it will start from the last searched word When the Scenario tool is opened it is possible to add create a new group or insert into an existing group a word or an Equivalent class directly in the Scenario by pressing the Add Insert butto
54. ord category is deemed significant when its occurrence frequency is far above average These results are constructed by comparing the statistics of the analyzed discourse regarding the category distribution with specific in built tables When you select a category the propositions concerned appear in the main window Displaying all word categories Click on the All word categories line of the Result frame or on the Show All word categories menu The result obtained with this function is similar to that of the previous one except that all Word categories are displayed even those that are less frequent or not significant For further details about these Word categories see chapter 4 Introduction to text analysis To view the References found with these categories we recommend that you use a Star graph see Graph properties below www semantic knowledge com 16 Tropes Reference Manual Lists of verbs and adjectives Click on the Verbs or Adjectives lines of the Result frame or use the Show Verbs Adjectives menu These two functions show by lessening frequency verbs and adjectives met in the analyzed text Every line is preceded by a meter indicating the number of words occurrences found These words are reduced to their canonical shape lemma Verbs are reduced to the infinitive Adjectives are presented in masculine singular Results Explain Extract Files 1j Scenario E dup ce
55. ot be detailed here Thus you obtain co occurrence statistics Relations of high reliability since it is not possible for two words to fit into the same grammatical proposition if they are not closely connected Propositional hashing is bound to involve errors propositions that are either too short or too long but this does not alter the results Ambiguity solving The automatic interpretation of words in any living language either written or spoken requires the solving of numerous ambiguities grammatical and syntactic the word mare for example corresponds to an adjective in un mare scandal and to a noun in Vara mergem la mare semantic the word lun for example can refer to our natural satellite or to month On average one word out of four is deemed ambiguous One of the main functions of this software is to solve these ambiguities by means of several problem solving algorithms Though a perfect result is impossible to achieve the error rate is low enough to guarantee an accurate analysis of your text Word categories The verbs are either factive i e expressing actions a face a munci a umbla etc Stative i e expressing states or concepts of possession a fi a sta etc reflexive a k a declarative i e expressing a statement about circumstances beings objects etc a g ndi a crede etc Connectors coordinating and subordi
56. owledge com 41 Tropes Reference Manual Terminology extraction The terminology extractor is capable of automatically identifying most significant expressions and compounds as well as all nouns not classified in the existing Scenario This tool is useful both for rapidly enriching the Scenarios of the software for example by grouping together all acronyms and the expressions corresponding to them and for obtaining a more precise classification proposing for example to hard wire terms causing ambiguity problems and or which might generate noise in the list of Relations The terminology extractor serves a triple purpose 1 It automatically extracts from the text all compounds i e repeated sequences of terms which contain at least one noun and are linguistically coherent which might prove interesting for purposes of analysis 2 It suggests a list of references to complement the Scenario and or draws up a list of everything that has not been classified as yet 3 It speeds up the construction of the Scenario The terminology extractor is semantically linked to the Scenario that is to say that when you select a family of terms Tropes will automatically try to position the Scenario tool on the group that seems most suitable to accommodate the selected expression The software can also perform an automatic search for a family of expressions in the text These two semantic linking functions can be deactivated cf
57. rumuse ea muzicii vechi ce se Show every pertinent groups of your Scenario p M_caragiale_remember f cea la noi de dimineata p n seara N p dit de o dulce aromeal imi l sam vis rile s nasc si s se topeasc in voie in noianul de armonii sublime At this stage you can use Semantic groups in the same way as Equivalent classes you can visualize the various types of graphs the groups placed in the position of Actants or Acted etc When you display these results you can use the toolbar at the bottom of the Tropes result window and a popup menu right click with your mouse to move around in the arborescence by displaying or hiding the branches commands Reduce all Expand all and to change the sorting order of the Scenario ay alle e The semantic classes in a Scenario are indicated by a checkbox in the result lists By this means it is possible to see at once if a class has been taken into account in your classification In the example below it will be seen that fapt and f nt n are classified in the Scenario while Tiergarten and Ruysdael are not E References YY Scenario Y Relations Y Frequent word categories JR M Actant Acted 0003 tiergarten 0003 lord 0003 ruysdael 7 0003 mare 7 0003 fapt v 0003 f nt n 7 0003 int mplare www semantic knowledge com 38 Tropes Reference Manual The methodology of Scenario design You may use a number of approaches when desi
58. s area and star show the Helations between the Equivalent classes They are oriented the classes on the left of the central class in red are its predecessors those on the right its successors The first graph displays the classes in the form of Areas wW floare ey k w v bx res a tot RA Each Equivalent class appears as a sphere whose surface is proportional to the number of words it contains Graph The distance between the central class and the other classes is proportional to the number of Relations connecting them in other words when two classes are close together they share many Relations and when they are far from one another they share few Relations If we take up the metaphor about the planetary system we can say that there is a central body Equivalent class around which planets Equivalent classes having Relations with the central class of various sizes according to the number of word occurrences they contain revolve more or less closely are more or less frequently used together Notes 1 The overlapping of two spheres has no particular significance 2 Word categories cannot be displayed in the area mode www semantic knowledge com 22 Tropes Reference Manual The Star graph displays the Relations between the Equivalent classes or between a Word category and an Equivalent class In the above example the albastru class central point is preceded
59. s consists in revealing the framework of a text i e its meaning This necessarily implies two things First there must be a theoretical conception of the text this must describe both the textual organization of the things that are said and the structural organization of the thought processes of the people who say them Secondly it implies the use of a tool derived from this theoretical conception and which rigorously excludes the subjectivity of the investigator at least until the analysis is finished We now propose to introduce you to such a tool Tropes www semantic knowledge com 6 Tropes Reference Manual T ropes CHAPTER 1 Analyzing a text www semantic knowledge com Tropes Reference Manual Saving a document in text format You must save the documents in the text format Microsoft Word files UTF 8 Windows HTML web pages RTF or other These documents must have a text file extension myfile doc WebPage htm etc Limitations may exist for some of these formats Consult the software user s manual for further details We recommend that you save your texts in the Text only UTF 8 or web page format HTML To carry out a file conversion use the Text only option of the Save as command of your word processor You can save web pages on your hard drive by means of your web browser or of a web spider The text may include punctuation marks capitals or special characters such as parentheses num
60. splay check both the Actants and Acted boxes The identification of Actants and Acted constitutes one of the essential steps in text analysis In fact when a significant Heference field or a Reference clearly appears in the position of Actant percentage above 6096 it is assumed that the notion it represents carries out the action Otherwise when a significant field or a Heference clearly appears in the position of Acted it is assumed that the notion it represents is subjected to the action www semantic knowledge com 14 Tropes Reference Manual Which elements are frequently connected Click on the Relations line or use the Show Relations command This function displays in decreasing frequency the strong Relations between the various Equivalent classes Each Helation is preceded by a counter showing its occurrence frequency within the studied text The Relations show which Equivalent classes are frequently connected i e found in the same proposition within the text analyzed To display the propositions corresponding to a given Relation click on the line of your choice Relations are oriented according to the occurrence order of the words comprising them By default Relations are built on the References lt is possible to define the construction level of the Relations by using the Tools Analysis options command see Analysis options below There is little room for chance in the display of Relations
61. ssing events that are essential to the progression of the story causal attributions of consequences results aims To extract these propositions Tropes carries out a complex Cognitive Discursive Analysis processing CDA To simplify matters let us say that each proposition of the text is allotted a score depending on its relative weight its occurrence order and its argumentative role The propositions are then sorted out according to their respective scores To enable you to control the amount of displayed propositions and to insure that the result obtained reflects the text analyzed Tropes provides the means to adjust the contraction rate of the text see Analysis options below It must be stressed that the Most Characteristic Parts of text offer significance only when studying a monolithic and structured discourse of moderate length In no circumstances will they constitute a summary of the text this would require a rewriting of the text www semantic knowledge com 12 Tropes Reference Manual Reference fields Click on the Reference fields 1 line of the Result frame or use the Show Reference fields 1 menu This function displays in decreasing frequency the Reference fields of the words in the text Each line consists of a field preceded by a counter showing the number of words contained within this particular field Only significant fields are displayed The Reference fields represent the context and group tog
62. stuffs that interests you on the other hand it would be more appropriate to class pepene galben and pepene ro u as fruits and castravete dovlecel among the vegetables In other contexts you may wish to differentiate between large companies and SMEs between toxic substances and medicines or between political personalities and their opponents Or indeed between what interests you and what you consider of secondary importance It is essential to use a Scenario if a text is to be analyzed correctly In most cases you will need to rework classifications correct any anomalies and personalize your analyses Furthermore the dictionaries of Tropes are constantly evolving and you can download new versions from the publisher s website You then conserve your personalized Scenarios even when you update your software When you install a new version analysis becomes more refined and you have the benefit of new classifications but you do not lose your work which is preserved in your Scenarios Tropes is supplied with several predefined Scenarios which correspond to different approaches to the classification of your documents 1 comprehensive with Scenario Concepts which groups references under broad themes similarly to a mass market general thesaurus 2 detailed with Scenario Concepts detailed which groups references under a larger number of themes on the lines of an encyclopedia 3 highly spec
63. t detected any significant Actant and this fact cannot be explained by the intensive use of personal pronouns Important note because of inner technical limits of the software some Heferences classes may not be displayed if the text is very long www semantic knowledge com 56 Tropes Reference Manual Analysis of heterogeneous utterances open questions dispatches enumerations etc The following notes concern all heterogeneous corpora obtained by collecting within the same file utterances coming from numerous individuals and without linear coherence i e it is not the discourse of a single narrator or an interaction between several interlocutors respecting a logical sequence or a strict chronological order Since the propositional hashing made by Tropes is based entirely on grammatical rules you must use a non ambiguous punctuation mark question or exclamation mark to force the software to separate the different utterances for example you can add an exclamation mark at the end of every answer to an Open question Market research in order to separate it from the next one If the corpus includes answers to several questions you will have to use Borders to group the answers together and or to separate the answers from the questions You will then analyze each answer separately If you have an indicator enabling you to form your corpus according to an external variable geographic area type of population period etc
64. tegories For example you can compare the respective weights weighted utilization rates and also the positions Actant Acted of the Equivalent classes the occurrence chronology of the main themes Bundles Episodes and Distribution graphs the co occurrence frequency of the References Star and Area graphs Relations Connection rate of the Helations Scenarios the various types of action through the analysis of the verbal categories Word categories Styles and Settings the type of logic at work and of involving through the analysis of Connectors and Modalities Word categories Bundles Episodes and in general all propositions enabling the introduction of the main characters and themes Most Characteristic Parts of text www semantic knowledge com 59 Tropes Reference Manual T ropes CHAPTER 5 Appendices www semantic knowledge com 60 Tropes Reference Manual Files conversion Observations about files format conversions Format ASCII The software uses Windows API function OemToChar to i convert this format in ANSI ISO 8859 1 HTML HTM See XML and SGML remarks below for HTML Hypertext HTML Markup Language file formats conversion The Apple Macintosh Latin character sets are converted to Pacino ANSI SO 8859 1 using the Windows API The software makes a conversion of Microsoft Word 97 2003 files using the 32 bits IFilter divers on your system Besides t
65. the distribution of the occurrence frequency of the categories observed in the text with linguistic production norms These norms have been elaborated after studying a great number of different texts They are stored into specific in built tables www semantic knowledge com 54 Tropes Reference Manual Equivalent classes and Relations between equivalents The Equivalent classes group together closely related References common nouns proper nouns trademarks appearing frequently throughout the text For example tat and mam are grouped together into the familie class The Reference fields group together the words comprising the Equivalent classes in order to enable the software to elaborate a representation of the context To achieve this the Semantic equivalents dictionary of Tropes is composed of three different classification levels At the lower level are the Heferences which are next merged more broadly into Reference fields 2 which in turn are merged into Reference fields 1 animale animale animale animale animale animale animale animale animale animale animale mamifere mamifere mamifere mamifere mamifere mamifere mamifere mamifere mamifere mamifere mamifere irbis irbis irbis irbis irbis irbis irbis irbis irbis irbis irbis irbis irbisi irbisii irbisilor irbisul irbisului leopardul z pezilor leopardului z pezilor leoparzii z pezilor leoparzilor z pezilor panthera
66. ur ns i s l colind ca odinioar nu mai mergea Oboseam repede i oboseala putea inlesni reivirea bolii M am resemnat dar c t va vreme a sta pe acas jertf de care m desp gubea in parte frumuse ea muzicii vechi ce se f cea la noi de diminea a p n seara N p dit de o dulce aromeal imi l sam vis rile s nasc i s se topeasc n voie n noianul de armonii sublime uit ndu m pe fereastr cu ochii pe jum tate nchi i cum unduiau curcubeie in pulberea fluid a f nt nii din larga piat gr din Lina boare a asfintitului leg na ciucuri purpurii ai trandafirilor ag tati pe terasa casei din fa purt ndu le mireasma p n la mine Seara da insufletire umbrelor in oglinzi tainic treceau fiori Acesta era ceasul pe care l a teptam ca s admir col ul cel mai frumos al pietei un petec de p dure r mas neatins in plin orasstc tiva b tr ni copaci frunzosi si sumbri vrednici s slujeasc de izvod celor mai cu faim me teri ai zugr veli i reg seam chiar la Muzeul Frederic ntr o cadr de Ruysdael el aceiasi copaci stufosi adumbrind l ng o c dere de ap un castel in ruin Odat nu puteam trece pe dinaintea ei f r a m opri indelung Privind o g ndul mi se pierdea f r sf rsit in f r ma i de cer v n t cu zare ad nc E inn scut in mine drojdie de str vechi eres o iubire p g n si cucernic pentru copacii b tr ni Lor le datoresc inspiratii mult nobil
67. uracy the essential propositions of a corpus we recommend that you start with a rather low threshold i e that you display many Characteristic parts of text and then raise it gradually until you strike a balance between the amount of displayed propositions and the pertinence of the result The Use the Scenario on all word categories option enables you to require the software to convert all the words entered in the semantic Scenario into substantives or References see related chapter When this box is checked it is possible to enter as items and display in the Scenario words that do not belong to the substantive category For example you can group together adverbs according to various themes You can also use this option to force the software to consider as substantives words that are not filed under this particular category for instance if you analyze a text presenting two characters DI Negru and DI Ro u you can enter Negru and Ro u in your Scenario so that they will be counted as References To validate your choice press the Accept button Otherwise if you do not wish to modify your analysis options press the Cancel button Caution when you check the Use the Scenario on all word categories box all words subsequently entered in the Scenario will be converted into substantives References at the end of the automatic analysis of the text This has several consequences on the operation of the s
68. urile cele mai dulci si mai parfumate lil 0052 existen asemenea unor nestimate topite at t toare de vis ri mu m S rea n ochi una e floarea de c mp alta floarea de gr din Acum fie c Bi 0042 spa iu 0032 intelect 0025 imbrac minte_si_inc lt minte xx 0023 statele_lumii 0023 materie 0019 ordine corp 0018 cantitate ml 0017 s n tate si boal 4 n jo gd c JEE JMil Se PRA tlel 4 e found 0077 equivalents of corp in this text B 11 E A a Note to detect these Reference fields the software uses a semantic equivalents dictionary which does not contain all of the Romanian words see Note on Equivalent classes below only the most significant substantives of your text will be displayed along with some proper nouns References what is the text about Click on the References line of the Result frame or use the Show References command This function displays in decreasing frequency the References of the words in the text Each line consists of a Heference preceded by a counter showing the number of www semantic knowledge com 13 Tropes Reference Manual words contained within this particular Reference Only significant References are displayed The References group together closely related common and proper nouns into Equivalent classes for example ochi and m n are grouped together into the corp class
69. ving the Scenario box from the Localize frame on the right in the dialog box www semantic knowledge com 43 Tropes Reference Manual Lastly the terminology extractor is provided with an Options tab with which you can fine tune the level of extraction Terminology extraction C Compounds Unclassified references Show all Filter C Show the most significant terms Show all Over to you www semantic knowledge com 44 Tropes Reference Manual T ropes CHAPTER 3 Borders www semantic knowledge com 45 Tropes Reference Manual Corpus segmentation Tropes is equipped with a tool called Borders designed to automatically segment a corpus Within the same text Borders can be used to automatically separate multiple actors an interviewer and an interviewee populations chapters of a book etc The use of Borders may require a preliminary coding of the documents A Border starts from where it has been located in the text and ends where the next Border has been located For example if p narator and p cucoana are Borders the sequence below delimits four parts of a text p narator Frumusel c tel aveti zic eu cocoanei dup c teva momente de t cere da raul p cucoana As nu e r u zice cocoana p n se nyat cu omul dar nu stiti ce cuminte si fidel este si destepti Ei bine e ca un om frate p narator Madam pentru Dumnezeu tineti l sa nu se dea la mine eu su
70. when the display applies to a specific part of the text i e when all the propositions are not displayed It can also be used to store temporarily a passage of particular interest to you To quit this dialog use the system menu in the top left corner of the window www semantic knowledge com 10 Tropes Reference Manual What is the text Style Click on the Text Style line of the Result frame or use the Show Text Style menu The software makes a diagnosis of the Text Style and of its Setting according to the statistical indicators retrieved during the analysis Here are the possible Styles Style Explanation Argumentative the speaker involves himself argues explains or analyzes in order to try to convince the interlocutor Narrative a narrator states a series of events happening at a given time and in a given place Enunciative the speaker and the interlocutor establish a mutual relation of influence make their standpoints known Descriptive a narrator describes identifies or classifies something or somebody Here are the possible verbal Settings The Setting is expressed by means of Dynamic action In the real verbs conveying the idea of being and having Involving the narrator verbs helping to make a statement about a given state an action Involving with I numerous pronouns in the first person singular I me myself Also you will immediately know whether or not notions a
71. xt frame and drag it onto the Scenario Use the Ctrl and Shift keys to control the addition or the insertion during this operation The Result popup menu right click with the mouse also contains two functions linked to the Scenario The command Aad to the Scenario creates an entry having the same group name as the selected Equivalent class The Insert in the Scenario command creates an entry by using the group name currently displayed in the Scenario Lastly you can create a new entry in the Scenario manually from the Search Ada dialog box Just type a word select a group and press the Scenario button You can choose to add a word or an Equivalent class to the Scenario It is possible to switch from the Insert function to the Add function and vice versa by checking a box located at the bottom of the Search Ada dialog www semantic knowledge com 34 Tropes Reference Manual Type a word m r Connect it to l Itself this word C Asemantic class v mar mar Scenario mar m r fruct L sfruct plante L gt plante mar mar rozacee L srozacee plante Search Y Fromthetop v Whole word only Scenario gt gt insert C Add als All the parts of the Tropes Graphic Interface contain popup menus right click with the mouse which enable easy addition insertion of words or Equivalent classes in the Scenario The Save button
72. yed at the top of the screen and the Episode it belongs to is automatically selected Should other Bundles of the same kind have been detected they will be highlighted Below we can see that the text example on Hemember txt begins with Bundles about sear arbore t n r etc and that it ends with Bundles about canal strain aubrey istorie etc DIO Torp Y Mod Mander qa me Prnt 7 7 7 7 3 888 773 7000 A Pronoun r ConnectorDisiunctModaity Manner ___ pod ___ _ Eonnector Opposition l 3 psear f ConnectorCondiioh er Pronoun T Pronownrr E muzeu i ModaltyMannef p r 5 noapte _ Modality Negation a ul a rU D n n un p cod NN Modality Manner inel 5 Modality FlaceConnector Cause Connector Opposition Modality Place Connector Case Pronoun T CH Modalky Time a Connector Opp si Manner Modality Negation Profloun F i Modaliy Neo mai jbtor Cause _ anal _Modgalty Manner Conhectok Cause _avut _ Pron un Thou MR i d i H EE d A MadalityiManner Modality Negation 5 Confiector Cause If there is not enough room on the screen to display all of the Bundles Tropes will try to exclude the less significant ones those containing fewer words You can avoid the congestion of this graph by building it from a Scenario see Analysis options Construction base for the Relations or by choosing a high Class detection thresh

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