UrduGram: Towards a Deep, Large-Coverage Grammar for Urdu and Hindi
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- Nigel James
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1 UrduGram: Towards a Deep, Large-Coverage Grammar for Urdu and Hindi Tafseer Ahmed, Tina Bögel, Miriam Butt, Annette Hautli, Ghulam Raza, Sebastian Sulger and Veronika Walther Universität Konstanz FB Kolloquium, May /60
2 Preview 1 Urdu & the UrduGram Project 2 Urdu Transliterator 3 Syntax 4 Semantics 2 /60
3 Urdu & the UrduGram Project Urdu Urdu is 3 /60
4 Urdu & the UrduGram Project Urdu Urdu is a South Asian language spoken primarily in Pakistan and India 3 /60
5 Urdu & the UrduGram Project Urdu Urdu is a South Asian language spoken primarily in Pakistan and India descended from (a version of) Sanskrit (sister language of Latin) 3 /60
6 Urdu & the UrduGram Project Urdu Urdu is a South Asian language spoken primarily in Pakistan and India descended from (a version of) Sanskrit (sister language of Latin) structurally identical to Hindi (spoken mainly in India) 3 /60
7 Urdu & the UrduGram Project Urdu Urdu is a South Asian language spoken primarily in Pakistan and India descended from (a version of) Sanskrit (sister language of Latin) structurally identical to Hindi (spoken mainly in India) together with Hindi the fourth most spoken language in the world ( 250 million native speakers) 3 /60
8 Urdu & the UrduGram Project Urdu and Hindi The two languages are regarded as structurally identical: 4 /60
9 Urdu & the UrduGram Project Urdu and Hindi The two languages are regarded as structurally identical: syntax/morphology are practically identical 4 /60
10 Urdu & the UrduGram Project Urdu and Hindi The two languages are regarded as structurally identical: syntax/morphology are practically identical vocabulary is practically identical (Urdu: borrowed from Persian/Arabic; Hindi: borrowed from Sanskrit) 4 /60
11 Urdu & the UrduGram Project Urdu and Hindi The two languages are regarded as structurally identical: syntax/morphology are practically identical vocabulary is practically identical (Urdu: borrowed from Persian/Arabic; Hindi: borrowed from Sanskrit) main difference is in the script 4 /60
12 Urdu & the UrduGram Project Urdu and Hindi The two languages are regarded as structurally identical: syntax/morphology are practically identical vocabulary is practically identical (Urdu: borrowed from Persian/Arabic; Hindi: borrowed from Sanskrit) main difference is in the script We are developing a single grammar and lexicon for both of the languages! 4 /60
13 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz 5 /60
14 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi 5 /60
15 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi Grammar is part of the ParGram project 5 /60
16 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi Grammar is part of the ParGram project Collaborative, world-wide research project 5 /60
17 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi Grammar is part of the ParGram project Collaborative, world-wide research project Devoted to developing parallel LFG grammars for a variety of languages 5 /60
18 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi Grammar is part of the ParGram project Collaborative, world-wide research project Devoted to developing parallel LFG grammars for a variety of languages Features and analyses are kept parallel for easy transfer between languages 5 /60
19 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi Grammar is part of the ParGram project Collaborative, world-wide research project Devoted to developing parallel LFG grammars for a variety of languages Features and analyses are kept parallel for easy transfer between languages Languages involved: 5 /60
20 Urdu & the UrduGram Project Context of Work Computational LFG grammar in development in Konstanz Aim: large-scale LFG grammar for parsing Urdu/Hindi Grammar is part of the ParGram project Collaborative, world-wide research project Devoted to developing parallel LFG grammars for a variety of languages Features and analyses are kept parallel for easy transfer between languages Languages involved: English, German, French, Japanese, Norwegian, Welsh, Georgian, Hungarian, Turkish, Chinese, Indonesian, Urdu (among many others) 5 /60
21 Urdu & the UrduGram Project The ParGram Grammar Architecture 6 /60
22 Urdu & the UrduGram Project The Parallel in ParGram Analysis for transitive sentence in English ParGram grammar (F-Structure, Functional Structure ): 7 /60
23 Urdu & the UrduGram Project The Parallel in ParGram Analysis for transitive sentence in English ParGram grammar (F-Structure, Functional Structure ): "Nadya saw the book." PRED SUBJ OBJ CHECK 'see<[1:nadya], [113:book]>' PRED 'Nadya' CHECK _LEX-SOURCE morphology, _PROPER known-name NTYPE NSEM PROPER NAME-TYPE first_name, PROPER-TYPE name NSYN proper 1 CASE nom, GEND-SEM female, HUMAN +, NUM sg, PERS 3 PRED 'book' CHECK _LEX-SOURCE countnoun-lex NTYPE NSEM COMMON count NSYN common SPEC PRED 'the' DET DET-TYPE def 113 CASE obl, NUM sg, PERS 3 _SUBCAT-FRAME V-SUBJ-OBJ TNS-ASP MOOD indicative, PERF -_, PROG -_, TENSE past 57 CLAUSE-TYPE decl, PASSIVE -, VTYPE main 7 /60
24 Urdu & the UrduGram Project The Parallel in ParGram (cont.) Analysis for the same transitive sentence in Urdu ParGram grammar (F-Structure, Functional Structure ): 8 /60
25 Urdu & the UrduGram Project The Parallel in ParGram (cont.) Analysis for the same transitive sentence in Urdu ParGram grammar (F-Structure, Functional Structure ): "nadiyah ne kitab dekhi" PRED 'dekh<[1:nadiyah], [20:kitAb]>' PRED 'nadiyah' CHECK _NMORPH obl SUBJ OBJ CHECK NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE erg, GEND fem, NUM sg, PERS 3 PRED 'kitab' NTYPE NSEM COMMON count NSYN common 20 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _SUBCAT-FRAME V-SUBJ-OBJ, _VFORM perf LEX-SEM AGENTIVE + TNS-ASP ASPECT perf, MOOD indicative 42 CLAUSE-TYPE decl, PASSIVE -, VTYPE main 8 /60
26 Urdu & the UrduGram Project The Parallel in ParGram (cont.) Analysis for the same transitive sentence in Urdu ParGram grammar (F-Structure, Functional Structure ): "nadiyah ne kitab dekhi" PRED 'dekh<[1:nadiyah], [20:kitAb]>' PRED 'nadiyah' CHECK _NMORPH obl SUBJ OBJ CHECK NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE erg, GEND fem, NUM sg, PERS 3 PRED 'kitab' NTYPE NSEM COMMON count NSYN common 20 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _SUBCAT-FRAME V-SUBJ-OBJ, _VFORM perf LEX-SEM AGENTIVE + TNS-ASP ASPECT perf, MOOD indicative 42 CLAUSE-TYPE decl, PASSIVE -, VTYPE main Analyses are kept parallel where possible 8 /60
27 Urdu & the UrduGram Project The Parallel in ParGram (cont.) Analysis for the same transitive sentence in Urdu ParGram grammar (F-Structure, Functional Structure ): "nadiyah ne kitab dekhi" PRED 'dekh<[1:nadiyah], [20:kitAb]>' PRED 'nadiyah' CHECK _NMORPH obl SUBJ OBJ CHECK NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE erg, GEND fem, NUM sg, PERS 3 PRED 'kitab' NTYPE NSEM COMMON count NSYN common 20 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _SUBCAT-FRAME V-SUBJ-OBJ, _VFORM perf LEX-SEM AGENTIVE + TNS-ASP ASPECT perf, MOOD indicative 42 CLAUSE-TYPE decl, PASSIVE -, VTYPE main Analyses are kept parallel where possible Features are kept parallel where possible 8 /60
28 Urdu & the UrduGram Project The Parallel in ParGram (cont.) Demo: Large-Scale English ParGram Grammar 9 /60
29 Urdu & the UrduGram Project Computational Grammars - What For? The Motivation behind ParGram 10 /60
30 Urdu & the UrduGram Project Computational Grammars - What For? The Motivation behind ParGram The ParGram project is working on Deep Grammars 10 /60
31 Urdu & the UrduGram Project Computational Grammars - What For? The Motivation behind ParGram The ParGram project is working on Deep Grammars Provide detailed syntactic and semantic analyses 10 /60
32 Urdu & the UrduGram Project Computational Grammars - What For? The Motivation behind ParGram The ParGram project is working on Deep Grammars Provide detailed syntactic and semantic analyses Encode grammatical functions, tense, number etc. 10 /60
33 Urdu & the UrduGram Project Computational Grammars - What For? The Motivation behind ParGram The ParGram project is working on Deep Grammars Provide detailed syntactic and semantic analyses Encode grammatical functions, tense, number etc. Linguistically motivated 10 /60
34 Urdu & the UrduGram Project Computational Grammars - What For? The Motivation behind ParGram The ParGram project is working on Deep Grammars Provide detailed syntactic and semantic analyses Encode grammatical functions, tense, number etc. Linguistically motivated Usually manually constructed ( linguistic intuition) 10 /60
35 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications 11 /60
36 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: 11 /60
37 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications 11 /60
38 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications Web-Search 11 /60
39 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications Web-Search Question-Answering 11 /60
40 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications Web-Search Question-Answering Knowledge Representation 11 /60
41 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications Web-Search Question-Answering Knowledge Representation Text Summarization 11 /60
42 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications Web-Search Question-Answering Knowledge Representation Text Summarization Machine Translation 11 /60
43 Urdu & the UrduGram Project Computational Grammars - What For? Possible Applications Large-Coverage, Deep Computational Grammars can be useful for: Meaning-Sensitive Applications Web-Search Question-Answering Knowledge Representation Text Summarization Machine Translation Computer-Assisted Language Learning 11 /60
44 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com 12 /60
45 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com Semantic search engine 12 /60
46 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com Semantic search engine Uses large-scale English LFG 12 /60
47 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com Semantic search engine Uses large-scale English LFG Works on English Wikipedia 12 /60
48 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com Semantic search engine Uses large-scale English LFG Works on English Wikipedia Parses query and matches with parsed corpus 12 /60
49 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com Semantic search engine Uses large-scale English LFG Works on English Wikipedia Parses query and matches with parsed corpus Can give better results than regular search engines 12 /60
50 Urdu & the UrduGram Project Computational Grammars - What For? powerset.com Semantic search engine Uses large-scale English LFG Works on English Wikipedia Parses query and matches with parsed corpus Can give better results than regular search engines (Example: X was bought by Y vs. Y acquired X ) 12 /60
51 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: 13 /60
52 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: tokenizer 13 /60
53 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: tokenizer transliterator (Urdu & Hindi to Roman script) 13 /60
54 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) 13 /60
55 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) syntax (c- and f-structure) (xle) 13 /60
56 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) syntax (c- and f-structure) (xle) semantics (xfr ordered rewriting) 13 /60
57 Urdu & the UrduGram Project Our Overall Architecture Our parsing architecture currently looks like this: tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) syntax (c- and f-structure) (xle) semantics (xfr ordered rewriting) xle is the overall development platform, with the other modules (fst and xfr) being plugged into it. 13 /60
58 Urdu & the UrduGram Project Overview Overall Architecture tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) syntax (c- and f-structure) (xle) semantics (xfr ordered rewriting) 14 /60
59 Urdu Transliterator Aim of the transliterator Our aim is to build and integrate a transliterator that allows for both, Urdu and Hindi, to be parsed and generated with the same grammar. couplet by the poet Mirza Ghalib Urdu Hindi Romanized Script (the XLE grammar) Right now we are working on the Urdu-Roman transliterator. 15 /60
60 Urdu Transliterator Transliteration scheme An excerpt from our scheme table: Unicode Urdu character Latin letter Phoneme in transliteration scheme b /b/ p /p/ t /t/ T /ú/ ^ j /j/ ^ c / > Ù/ 16 /60
61 Urdu Transliterator Basic idea of the transliterator use finite state transducer to allow for generation and parsing. 17 /60
62 Urdu Transliterator Basic idea of the transliterator use finite state transducer to allow for generation and parsing. Urdu script: parsing generating ASCII: ba 17 /60
63 Urdu Transliterator Basic idea of the transliterator use finite state transducer to allow for generation and parsing. Urdu script: parsing generating ASCII: ba The same concept will be used to create a transliterator for Hindi/Devanagari 17 /60
64 Urdu Transliterator Basic idea of the transliterator use finite state transducer to allow for generation and parsing. Urdu script: parsing generating ASCII: ba The same concept will be used to create a transliterator for Hindi/Devanagari This way we can parse Urdu script and generate Hindi script (and vice versa) 17 /60
65 Urdu Transliterator Position of the transliterator the transliterator is composed with the tokenizer (separates the words within a sentence) 18 /60
66 Urdu Transliterator Position of the transliterator the transliterator is composed with the tokenizer (separates the words within a sentence) tokenizer and transliterator are placed in front of the morphology 18 /60
67 Urdu Transliterator Position of the transliterator the transliterator is composed with the tokenizer (separates the words within a sentence) tokenizer and transliterator are placed in front of the morphology Input Transliterator Output kitab Input kitab Morphology Output kitab+noun+fem+sg+count XLE /60
68 Urdu Transliterator Example The transliterator at this position works quite well: (1) larke boy ki kitab gen book The boy s book Problem: long sentences or highly ambiguous words (when looking at script) need some time to parse. 19 /60
69 Urdu Transliterator Problems of the script - an example The problem of the vowels... Diacritics represent short vowels Urdu script Roman script ba bi bu 20 /60
70 Urdu Transliterator Problems of the script - an example The problem of the vowels... Diacritics represent short vowels Urdu script Roman script ba bi bu (2) nadya ne yasin ko kitab dekhne di Nadya erg Yasin dat see let Nadya let Yassin see the book 20 /60
71 Urdu Transliterator Problems of the script - an example The problem of the vowels... Diacritics represent short vowels Urdu script Roman script ba bi bu (2) nadya ne yasin ko kitab dekhne di Nadya erg Yasin dat see let Nadya let Yassin see the book Unfortunately, these diacritics tend to be left out. 20 /60
72 Urdu Transliterator Consequences If the input is without diacritics, e.g.... Urdu script letter combination representation translation ktab kitab book 21 /60
73 Urdu Transliterator Consequences If the input is without diacritics, e.g.... Urdu script letter combination representation translation ktab kitab book.. then there are all kinds of possible combinations: kitab, kutaab, kitabu, ikataubi, ukitabia, akatabu, aukataib /60
74 Urdu Transliterator Consequences If the input is without diacritics, e.g.... Urdu script letter combination representation translation ktab kitab book.. then there are all kinds of possible combinations: kitab, kutaab, kitabu, ikataubi, ukitabia, akatabu, aukataib... (demo) 21 /60
75 Urdu Transliterator Solution In order to restrict this overgeneration the possible letter combinations need to be constrained: 22 /60
76 Urdu Transliterator Solution In order to restrict this overgeneration the possible letter combinations need to be constrained: which vowels are actually allowed to cooccur? ai, but not ia? 22 /60
77 Urdu Transliterator Solution In order to restrict this overgeneration the possible letter combinations need to be constrained: which vowels are actually allowed to cooccur? ai, but not ia? which consonants are actually allowed to cooccur? initial kr, but not gr? 22 /60
78 Urdu Transliterator Solution In order to restrict this overgeneration the possible letter combinations need to be constrained: which vowels are actually allowed to cooccur? ai, but not ia? which consonants are actually allowed to cooccur? initial kr, but not gr? certain combinations with semi-vowels or consonants are not allowed: a short vowel followed by v may not be followed by u or i 22 /60
79 Urdu Transliterator Solution In order to restrict this overgeneration the possible letter combinations need to be constrained: which vowels are actually allowed to cooccur? ai, but not ia? which consonants are actually allowed to cooccur? initial kr, but not gr? certain combinations with semi-vowels or consonants are not allowed: a short vowel followed by v may not be followed by u or i certain positions are prohibited: a word can never end in a short vowel or begin with a short vowel that is only represented with a diacritic 22 /60
80 Urdu Transliterator Solution write rules and filters out of these constraints and apply them to the transliterator (demo) 23 /60
81 Urdu Transliterator Solution write rules and filters out of these constraints and apply them to the transliterator (demo) Problem: these rules cannot be found in the literature - they are a product of extensive manual labor 23 /60
82 Urdu Transliterator Solution write rules and filters out of these constraints and apply them to the transliterator (demo) Problem: these rules cannot be found in the literature - they are a product of extensive manual labor However, the transliterator works quite well now Some sentences are still a little slow (but I keep looking for possible restrictions) continue with generation of Urdu and the Hindi transliterator 23 /60
83 Urdu Transliterator Overview Overall Architecture tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) syntax (c- and f-structure) (xle) semantics (xfr ordered rewriting) 24 /60
84 Syntax Syntax syntax component is at the core of Urdu grammar 25 /60
85 Syntax Syntax syntax component is at the core of Urdu grammar theoretical background: LFG 25 /60
86 Syntax Syntax syntax component is at the core of Urdu grammar theoretical background: LFG well-studied ( 30 years) framework with computational usability 25 /60
87 Syntax Syntax syntax component is at the core of Urdu grammar theoretical background: LFG well-studied ( 30 years) framework with computational usability c- and f-structures used for syntactic representation 25 /60
88 Syntax Syntax syntax component is at the core of Urdu grammar theoretical background: LFG well-studied ( 30 years) framework with computational usability c- and f-structures used for syntactic representation c-structure: basic constituent structure ( tree ) and linear precedence ( what parts belong together) 25 /60
89 Syntax Syntax syntax component is at the core of Urdu grammar theoretical background: LFG well-studied ( 30 years) framework with computational usability c- and f-structures used for syntactic representation c-structure: basic constituent structure ( tree ) and linear precedence ( what parts belong together) f-structure: encodes syntactic functions and properties 25 /60
90 Syntax Syntax CS 1: ROOT S KP VCmain NP V N hansi nadiyah "nadiyah hansi" PRED SUBJ CHECK 'hans<[1:nadiyah]>' PRED 'nadiyah' NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _SUBCAT-FRAME V-SUBJ, _VFORM perf LEX-SEM VERB-CLASS unerg TNS-ASP ASPECT perf, MOOD indicative 18 CLAUSE-TYPE decl, PASSIVE -, VTYPE main 26 /60
91 Syntax Syntax CS 1: ROOT S KP VCmain NP V N hansi nadiyah "nadiyah hansi" PRED SUBJ CHECK 'hans<[1:nadiyah]>' PRED 'nadiyah' NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _SUBCAT-FRAME V-SUBJ, _VFORM perf LEX-SEM VERB-CLASS unerg TNS-ASP ASPECT perf, MOOD indicative 18 CLAUSE-TYPE decl, PASSIVE -, VTYPE main current size: 53 phrase-structure rules, annotated for syntactic function (usual size of large-scale grammars: rules) 26 /60
92 Syntax Syntax CS 1: ROOT S KP VCmain NP V N hansi nadiyah "nadiyah hansi" PRED SUBJ CHECK 'hans<[1:nadiyah]>' PRED 'nadiyah' NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _SUBCAT-FRAME V-SUBJ, _VFORM perf LEX-SEM VERB-CLASS unerg TNS-ASP ASPECT perf, MOOD indicative 18 CLAUSE-TYPE decl, PASSIVE -, VTYPE main current size: 53 phrase-structure rules, annotated for syntactic function (usual size of large-scale grammars: rules) coverage: basic clauses with free word order, NP syntax, tense and aspect, causative verbs, complex predicates, relative clauses, passives, semantically-based case marking 26 /60
93 Syntax Discontinuous NPs in Urdu 1 Well known discontinuities 2 NP-internal discontinuity in Urdu 3 LFG implementation 4 Conclusion 27 /60
94 Syntax Extraction from DP (2) a. Er hat viele Bücher über Logik gekauft. He has many books on logic bought He has bought many books about logic. b. Bücher über Logik hat er viele gekauft. c. Über Logik hat er viele Bücher gekauft. (German) (3) mantiq=par nida=ne Ek kitab logic=loc.on Nida=Erg one book.f.3sg xarid-i he. buy-perf be.pres Nida has purchased a book on logic. (Urdu) 28 /60
95 Syntax Quantifier Float (4) a. They all have bought a car. b. They have all bought a car. (5) Am ali=ne bahut kha-e mango.pl Ali=Erg many eat-perf Ali ate many mangoes. (Urdu) 29 /60
96 Syntax Constituent-level discontinuities in Urdu NP-internal discontinuity Discontinuous NP Discontinuous AP 30 /60
97 Syntax When NP-internal discontinuity occurs in Urdu The NP-internal discontinuity in Urdu can occur when the argument-taking noun is modified by: argument-taking adjectives argument-taking specifier nouns 31 /60
98 Syntax Argument-taking adjectives in Urdu Nr. Type of Argument Example of Adjective Phrase (i) Dative Marked sadr=ko hasil president=dat possessed possessed by the president (ii) Ablative Marked adliyah=se xaif courts=abl afraid afraid of courts (iii) Locative Marked buxar=men mubtala fever=loc.in suffered suffered with fever (iv) Adpositional sihat=ke liye muzir health=gen for harmful harmful for health 32 /60
99 Syntax Simple examples of argument-taking nouns (6) a. istisna immunity b. muqaddamat=se istisna court-case.pl=abl immunity immunity from court-cases c. muqaddamat=se AInI istisna court-case.pl=abl constitutional immunity constitutional immunity from court-cases 33 /60
100 Syntax Simple examples of argument-taking nouns (7) a. barifing briefing b. salamti=par barifing security=loc briefing briefing on security c. salamti=par tafsili barifing security=loc detailed briefing detailed briefing on security 34 /60
101 Syntax Simple examples of argument-taking nouns (8) a. mutalba demand b. ArmI-cIf=sE mutalba army-chief=abl demand demand to the army-chief c. ArmI-cIf=sE qanuni mutalba army-chief=abl legal demand legal demand to the army-chief 35 /60
102 Syntax Examples of discontinuous NPs (9)a1. sadr=ko 1 hasil 1 muqaddamat=se 2 president=dat possessed court-cases=abl AInI istisna 2 constitutional immunity Constitutional Immunity from court-cases possessed by the president a2. [ NP [ AP [ KP sadr=ko] hasil][ KP muqaddamat=se] AInI istisna] b. muqaddamat=se 2 sadr=ko 1 hasil 1 AInI istisna 2 c. sadr=ko 1 muqaddamat=se 2 hasil 1 AInI istisna 2 d. *hasil 1 muqaddamat=se 2 sadr=ko 1 AInI istisna 2 36 /60
103 Syntax Hierarchical structure of AP in NP CS 1: NP KP AP AP N NP K KP A A istis2na N se NP K h2as3il AInI muqaddamat N ko s3adr Figure: Hierarchical structure of AP in NP 37 /60
104 Syntax Examples of discontinuous NPs (10) a1. ArmI-cIf=sE 2 salamti=par 1 barifing 1 =ka mutalba 2 army-chief=abl security=loc.on briefing=gen demand The demand to the army chief for briefing on security a2. [ NP [ KP ArmI-cIf=sE][ KP [ NP [ KP salamti=par] barifing]=ka] mutalba] b. salamti=par 1 ArmI-cIf=sE 2 barifing 1 =ka mutalba 2 38 /60
105 Syntax Examples of discontinuous NPs (11) [ NP [ KP ArmI-cIf=sE] [ KP [ NP [ KP mulki salamti=par] army-chief=abl of-country security=loc.on tafsili barifing]=ka] qanuni mutalba] detailed briefing=gen legal demand The legal demand to the army chief for a detailed briefing on security of the country 39 /60
106 Syntax LFG implementation of NP-internal discontinuity Scrambling of elements in oval possible with some constraints NP KP/PP A+ A N Spec(N)/Arg(N/A) Arg-taking-adj Arg-less-adj Head-noun Figure: Word Order in Noun Phrases of Urdu 40 /60
107 Syntax Implementation Issues Free word order in an NP Relating arguments with corresponding heads Head last constraint 41 /60
108 Syntax LFG instruments used Shuffle operator (, ): To accommodate free word order of different elements in the noun phrases. Non-deterministic operator ( $ ): Relating the corresponding arguments to the corresponding heads. Head Precedence Operator ( <h ): To make it sure that the head must not precede its arguments in the noun phrases. 42 /60
109 Syntax An excerpt from Grammar Rules NP KP*: { (^ ADJUNCT $ OBL)=! (^ ADJUNCT $ OBJ- GO)=! (^ OBL) =! (^ OBJ-GO) =! }, for scrambling AP*:! $ (^ ADJUNCT ) N : ^ =! KP*: { (^ ADJUNCT $ OBL)=! (^ ADJUNCT) <h (^ ADJUNCT $ OBL)... }... Figure: Grammar Rules 43 /60
110 Syntax C-structure for a discontinuous NP CS 1: NP KP KP AP AP N NP K NP K A A istis2na N ko N se h2as3il AInI s3adr muqaddamat Figure: C-structure 44 /60
111 Syntax F-structure for a discontinuous NP "s3adr ko muqaddamat se h2as3il AInI istis2na" 49 PRED OBL ADJUNCT 'istis2na<[34:muqaddamah]>' PRED 'muqaddamah' CHECK _NMORPH obl 34 CASE inst, GEND masc, NUM pl PRED 'h2as2il<[1:s3adr]>' PRED 's3adr' CHECK _NMORPH obl OBJ-GO NSEM COMMON count NTYPE NSYN common 1 CASE dat, GEND masc, NUM sg, PERS 3 CHECK _RESTRICTED - LEX-SEM GOAL + 39 ATYPE attributive PRED 'AInI' ATYPE attributive 44 <s [39:h2As2il] Figure: F-structure 45 /60
112 Syntax Summary Urdu is a typical language in which discontinuous NPs are found both at: Clause-level Constituent-level Constituent-level discontinuity in Urdu can be implemented in LFG framework by making use of: Shuffle operator (, ) Non-deterministic operator ( $ ) Head-precedence operator ( <h ) 46 /60
113 Syntax Overview Overall Architecture tokenizer transliterator (Urdu & Hindi to Roman script) morphology (fst) syntax (c- and f-structure) (xle) semantics (xfr ordered rewriting) 47 /60
114 Semantics Intro Aim: a large-coverage computational semantic analyzer on the basis of a deep syntactic analysis use f-structures as starting point apply xfr semantic rules from f-structure facts to a semantic representation (Crouch and King, 2006) judgment on the semantic well-formedness of a sentence The girl laughs. semantically well-formed #The tree laughs. semantically ill-formed we need lexical information about the words in a sentence 1 lexical resource for Urdu verbs more information on the verb and its arguments 2 general lexical resource for Urdu nouns, adjectives etc. 48 /60
115 Semantics Intro F-structure for nadiyah hansi (Nadya laughed). "nadiyah hansi" PRED SUBJ CHECK 'hans<[1:nadiyah]>' PRED 'nadiyah' NTYPE NSEM PROPER PROPER-TYPE name NSYN proper SEM-PROP SPECIFIC + 1 CASE nom, GEND fem, NUM sg, PERS 3 _VMORPH _MTYPE infl _RESTRICTED -, _VFORM perf LEX-SEM VERB-CLASS unerg TNS-ASP ASPECT perf, MOOD indicative 18 CLAUSE-TYPE decl, PASSIVE -, VTYPE main xfr semantic rule: PRED(%1, hans), SUBJ(%1, %subj), -OBJ(%1, %obj) ==> word(%1, hans, verb), role(agent, %1, %subj). 49 /60
116 Semantics Developing an Urdu VerbNet (1) following the methodology of the English VerbNet (Kipper-Schuler 2006) categorization of English verbs in 250 classes information on event structure and argument structure of verbs provides the general architecture for a VerbNet in any language e.g. parts of the entry for laugh in the English VerbNet 50 /60
117 Semantics Developing an Urdu VerbNet (2) Difficulty: resource sparseness of Urdu Approach 1: translating the entries in the English VerbNet to Urdu figure out problematic cases Approach 2: fully rely on corpus work extend tool for automatic subcategorization extraction (Ghulam, 2010) Can we benefit from a Hindi lexical resource? 51 /60
118 Semantics Hindi WordNet Facts: inspired in methodology and architecture by the English WordNet (Fellbaum 1998) 52 /60
119 Semantics Hindi WordNet developed at the Indian Institute of Technology, Bombay, India separated into four independent semantic nets verbs, nouns, adjectives and adverbs about verbs, nouns, adjectives and adverbs words are grouped according to their meaning similarity ( synsets ) 53 /60
120 Semantics Hindi WordNet Issues far less specific concepts than in the English WordNet Hindi WordNet: TOP Noun Inanimate Object Artifact kitab TOP Noun Inanimate Object Artifact mez English WordNet: entity physical entity object whole unit artifact creation product piece of work publication book entity physical entity object whole unit artifact instrumentatlity furnishing piece of furniture table 54 /60
121 Semantics Benefits for an Urdu VerbNet Preliminary experiments for Urdu/Hindi verbs Resources that we have: the database from Hindi WordNet a list of Urdu verbs out of Hindi verbs, we have found 534 verbs in an Urdu verb list (Humayoun, 2006) complex predicates are included in Hindi WordNet, but not in the Urdu wordlist total of around 700 Urdu verbs more than 2/3 of Urdu verbs are found all found verbs seem to be valid extract verb information from Hindi WordNet for the Urdu VerbNet 55 /60
122 Semantics Urdu Lexical Semantics Polysemy: An extreme case - eat expressions in Hindi/Urdu (Hook and Pardeshi, 2009): employing eat in idiomatic expressions about 160 eat expressions for Hindi/Urdu variety of uses due to loan translations from Persian 56 /60
123 Semantics Urdu Lexical Semantics h2asan=ne kek=ko khaya h2asan.erg cake.acc eat.perf.sg.masc Hasan ate the cake. eat= Agent, Theme inqilabi fikar zang kha jaegi revolutionary thought rust eat go.fut Revolutionary thinking will gather rust. eat (gather rust) = Patient, Theme is sal=ki mandi sheyar-bazar kha gayi this year.gen slowdown.fem stockmarket eat go.fut.fem This year s slowdown wrecked (lit. devoured) the stock market. eat (wreck) = Agent, Theme 57 /60
124 Semantics Urdu Lexical Semantics How do we approach polysemy in the computational semantics? extensive corpus work to find polysemous verbs assign different thematic roles to polysemous verbs? put all combinations in the Urdu VerbNet, but mark the original use? analysis for all sentences, mark idiomatic and semantically ill-formed sentences as such? 58 /60
125 Semantics Wrap up What we have talked about: architecture of the Urdu LFG Grammar ongoing work transliteration discontinuous NPs computational semantics challenges ahead Demo 59 /60
126 Semantics Thank you! 60 /60
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