1 / 50

Computational Grammars

Computational Grammars. Azadeh Maghsoodi. History. Before 1800 1800-1900 First 20s 20s World War II Last 1950s Nowadays. Before 1800. Traditional Grammar Correct Speech of a specific language Not scientific Rejected Useful issues: POS. 1800-1900. Indian-European languages

omer
Télécharger la présentation

Computational Grammars

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

  1. Computational Grammars Azadeh Maghsoodi

  2. History Before 1800 1800-1900 First 20s 20s World War II Last 1950s Nowadays

  3. Before 1800 • Traditional Grammar • Correct Speech of a specific language • Not scientific • Rejected • Useful issues: POS

  4. 1800-1900 • Indian-European languages • Language vs. Other languages • Language vs. its history

  5. Early 20s • Enough Philology! • Language in a specific time

  6. 20s • America & Western Europe • Intellectual Pattern • Understanding Processes in human being

  7. World War II • Math. Logic as a study tool • Computer invention caused new App • Abstract Mind model ends Behaviorism

  8. Late 1950 • Chomsky is coming! • Formal Language Theory • “Syntactic Structures” • Language Categories • Type 0: Natural (Irregular) • Type 1: Context sensitive • Type 2: Context free • Type 3: Regular

  9. Late 1950 (continue) • Chomsky followers professes: • Generative grammar: Accurate and definite enough for testing • Generative Grammars • Goal: Unaware knowledge of users • Biologic and inborn basis for linguistic abilities • Universal Grammar • Shared structures

  10. Nowadays • Motives • Discover human mind structure • Language process technology • Applications • Word processors • MT • Word predictors • Text predictors • UFIs / DB Queries • Information retrieval

  11. Syntactic Model Grammars Parse Algorithms

  12. Computational Grammars • Generative Grammars • Caused by Natural Language Theory • Introduced by Chomsky • Accurate and definite structures • Transformational grammar (TG) • Constraint-Based Lexicalist grammar (CBLG)

  13. TG • Less computational efficiency • Theoretical basis • Complex rules • Simple lexicons

  14. TG (continue) • Chomsky hierarchy & First TG • Standard Theory (1965) • Extended Standard Theory • Government & Binding Theory (1981-1988)

  15. Standard Theory • Sentence • Deep structure • Surface structure • Generative TG • Basic part • Produce deep structure • CFG • Transformational part • Transformational Rules

  16. Transformational Rules • Convert deep structure to surface structure • Transformational Rule ~ Transformation • Example: (same deep structures) • (i) The boys place the book on the table. • (ii) The boy has placed the book on the table. • (iii) Did the boy place the book on the table?

  17. Transformational Rules (example) • A deep structure:

  18. Transformational Rules (example) Move Transformation • To produce yes/no question: • Using a Move Transformation • S[NP VP [AUX V NP]] S[AUX NP VP[V NP]]

  19. Government and Binding Theory (GB) • Universal grammar theory • Learning a language = confirming a small set of parameters + learning lexicons • Move α: deep structure to surface structure • ‘Move α’ moves anything to anywhere • Some constraints correct ‘Move α’

  20. GB (continue) Lexicons Deep Struct Move-α Surface Struct Stylistic & Phonological Rules LF Move-α Phonological Form Logical Form

  21. GB (continue) • Minimalist Program (MP) • Choose the best candidate instead of direct production • Under study

  22. CBLG • Based on TGs • Increase computational efficiency of grammars • Simple rules • Complex lexicons • Psychological • Computational

  23. CBLG (continue) • Constraint-Based architecture • Constraint satisfaction more important than transformational derivation • Strict lexicalism • Lexicons: syntactic atoms of a language • Independent Internal structure from syntactic constraints

  24. CBLG (continue) • Surface structures are produced directly • Most computational grammars are CBLG

  25. Computational Grammars • Unification grammar (UG) • Categorical grammar (CG) • Dependency grammar (DG) • Link grammar • Lexical/Functional grammar (LFG) • Tree Adjoining grammar (TAG) • Generalized Phrase Structure grammar (GPSG) • Head Driven Phrase Structure grammar (HPSG)

  26. Unification Grammar (UG) • Lots of CBLs are UG • Augmented CFG • CFG can’t recognize long distance dependencies • A generalized form of CFG + A set of features • Augmented Transition Network (ATN) • Definite Clause Grammar (DCG) • Unification Grammars

  27. UG (continue) • Unification Grammars • Feature structures are extended • No need to CFGs • Grammar ~ A set of constraints between feature structures • Key concept: Subsumption relation

  28. UG (continue) CAT verb ROOT cry CAT verb ROOT cry CAT verb VFORM present VFORM present (Unificator)

  29. UG (example) S NP VP • Unification grammar: X0 X1 X2 CAT 0 = 5 CAT 1 = NP CAT 2 VP AGR 0 = AGR 1 = AGR 2 VFORM 0 = VORM 2

  30. UG (continue) • More grammar information are stored in lexicons • Less grammar rules • Using DAGs

  31. ATN Grammar • Transitive network ~ Expanded Finite-State machine • ATN Grammar ~ A set of transitive networks • Features • Constraints

  32. Categorical Grammar (CG) • Lots of bases are omitted • No difference between lexicons and none-lexicons • Part Of Speech is replaced by some complex category • NP/S : NP is on the right • NP\S : NP is on the left

  33. CG (example) Peter : NP Likes : (NP\S)/NP Peanuts : NP Passionately : (NP\S)\(NP\S) Peter likes peanuts passionately.

  34. CG (example)

  35. Dependency Grammar (DG) • American linguists • Based on TGs • Dependencies between words • Dependency tree

  36. Link Grammar • Planarity phenomenon • Legal sequence of words: • Satisfy local necessities (satisfaction) • No crossed conjunctions (planarity) • One connected graph (connectivity) • CFG • Lexical grammars • Grammar is distributed between words • Probability models • Voice recognition • Hand-written recognition

  37. Link Grammar (example) linking requirements:

  38. Link Grammar (example) linking requirements are satisfied

  39. Link grammar (example) Not part of a language

  40. Lexical-Functional Grammar (LFG) • Unification grammar • Not TG • ATN research and its deficiencies introduced LFG • Group structures • 4 structures

  41. Tree Adjoining Grammar (TAG) • Between CFG and CSG • Grammar rules are a set of initial trees • Initial trees are anchored trees • Two main operations: • Substitution • Adjoin • High accuracy

  42. TAG (example) S VP S NP VP + VP ADV  NP VP V NP VP ADV V NP

  43. TAG (continue) • High accuracy • Apps in NLP • MT • Information retrieval • …

  44. Generalized Phrase Structure grammar (GPSG) • Only CFLs • CFG Rules • Immediate Dominance (ID) • Linear Precedence (LP)

  45. Head Driven Phrase Structure grammar (HPSG) • Lexical grammar • Based on unification • Increase computational potency of GPSG • Simple CFG • Complex lexicons

  46. Applications

  47. Parse Algorithms • Top-Down parsing • Bottom-Up parsing (*)

  48. Parse Algorithms • Top-Down parsing • Chart parser • Dynamic Programming • Recursive Transition Network (RTN) • ATN grammar • LR parser • Shift-Reduce algorithms • Cocke-Younger-Kasami parser (CYK) • Dynamic Programming • CNF grammar

  49. Efficient Algorithms • Chart parser • CYK parser

  50. Questions???

More Related