Linguistics 187: Grammar Engineering

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Linguistics 187 Grammar Engineering

• Ron Kaplan and Tracy King

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Administrivia

• Schedule Office hours
• Requirements
• Overview

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Applications of Language Engineering
Shallow
Synthesis
Broad
Domain Coverage
Narrow
Deep
Low
High
Functionality
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Grammar engineering for deep processing

• Draws on theoretical linguistics, software
  engineering
• Theoretical linguistics gt papers
• Generalizations, universality, idealization
  (competence)
• Software engineering gt programs
• Coverage, interface, QA, maintainability,
  efficiency, practicality
• Grammar engineering
• GrammarTheory ProgramProgramming language
• Reflect linguistic generalizations
• Respect special cases of ordinary language
• Deal with large-scale interactions
• Theory/practice trade-offs

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What is a shallow grammar

• often trained automatically from marked up
  corpora
• part of speech tagging
• chunking
• trees

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POS tagging and Chunking

• Part of speech tagging
• I/PRP saw/VBD her/PRP duck/VB ./PUNCT
• I/PRP saw/VBD her/PRP duck/NN ./PUNCT
• Chunking
• general chunking
• I begin with an intuition when I read a
  sentence, I read it a chunk at a time.
  (Abney)
• NP chunking
• NP President Clinton visited NP the Hermitage
  in NP Leningrad

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Treebank grammars

• Phrase structure tree (c-structure)
• Annotations for heads, grammatical functions

Collins parser output
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Deep grammars

• Provide detailed syntactic/semantic analyses
• LFG (ParGram), HPSG (LinGO, Matrix)
• Grammatical functions, tense, number, etc.
• Mary wants to leave.
• subj(want1,Mary3)
• comp(want1,leave2)
• subj(leave2,Mary3)
• tense(want1,present)
• Usually manually constructed
• linguistically motivated rules

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Why would you want one

• Meaning sensitive applications
• overkill for many NLP applications
• Applications which use shallow methods for
  English may not be able to for "free" word order
  languages
• can read many functions off of trees in English
• SUBJ NP sister to VP S NP Mary VP left
• OBJ first NP sister to V S NP Mary VP saw
  NP John
• need other information in German, Japanese, etc.

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Deep analysis matters if you care about
the answer

• Example
• A delegation led by Vice President Philips, head
  of the chemical division, flew to Chicago a
  week after the incident.
• Question Who flew to Chicago?
• Candidate answers
• division closest noun
• head next closest
• V.P. Philips next

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Traditional Problems

• Time consuming and expensive to write
• Robustness
• want output for any input real-world
  applications
• Ambiguity
• Efficiency
• Interfaces to other application components

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Why deep analysis is difficult

• Languages are hard to describe
• Meaning depends on complex properties of words
  and sequences
• Different languages rely on different properties
• Errors and disfluencies

• Languages are hard to compute
• Expensive to recognize complex patterns
• Sentences are ambiguous
• Ambiguities multiply explosion in time and
  space

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How to overcome this

• Engineer the deep grammars
• theoretical vs. practical
• what is good enough
• Integrate shallow techniques into deep grammars
• Experience based on broad-coverage LFG grammars
  (ParGram project)

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Robustness Sources of Brittleness

• missing vocabulary
• you can't list all the proper names in the world
• missing constructions
• there are many constructions theoretical
  linguistics rarely considers (e.g. dates, company
  names)
• easy to miss even core constructions
• ungrammatical input
• real world text is not always perfect
• sometimes it is really horrendous

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Real world Input

• Other weak blue-chip issues included Chevron,
  which went down 2 to 64 7/8 in Big Board
  composite trading of 1.3 million shares Goodyear
  Tire Rubber, off 1 1/2 to 46 3/4, and American
  Express, down 3/4 to 37 1/4. (WSJ, section 13)
• The croaker's done gone from the hook
  (WSJ, section 13)
• (SOLUTION 27000 20) Without tag P-248 the W7F3
  fuse is located in the rear of the machine by the
  charge power supply (PL3 C14 item 15.
  (Eureka copier repair tip)

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Missing vocabulary

• Build vocabulary based on the input of shallow
  methods
• fast
• extensive
• accurate
• Finite-state morphologies
• Part of Speech Taggers

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LFG and XLE This course

• LFG a theory of grammar
• XLE a parsing/generation engine for LFG grammars

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Different patterns code same meaning
The small children are chasing the dog.
English Group, order
Japanese Group, mark
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Different patterns code same meaning
The small children are chasing the dog.
LFG theory minor adjustments on universal theme
English Group, order
Japanese Group, mark
Chase(small(children), dog)
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LFG architecture
Modularity

• C-structures and f-structures in piecewise
  correspondence.

S
f
NP
VP
John
V
NP
likes
Mary
Formal encoding of grammatical relations
Formal encoding of order and grouping
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LFG grammar
Rules
Lexical entries
S ? NP VP (? SUBJ)? ??
John NP (? PRED)John (?
NUM)SG likes V (? PRED)likeltSUBJ, OBJgt
(? SUBJ NUM)SG (? SUBJ PERS)3
VP ? V NP ? ? (? OBJ)?

• Context-free rules define valid c-structures
  (trees).
• Annotations are instantiated at tree nodes to
  give equational constraints that corresponding
  f-structures must satisfy.
• Satisfiability of constraints determines
  grammaticality.
• F-structure is solution for equations (if
  satisfied).

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Rules as well-formedness conditions
S
SUBJ
NP
VP
A tree containing S over NP - VP is OK if
F-unit corresponding to NP node is SUBJ of f-unit
corresponding to S node The same f-unit
corresponds to both S and VP nodes.
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Inconsistent equations Ungrammatical

• Whats wrong with They walks ?

f v and (v SUBJ NUM)SG gt (f SUBJ
NUM)SG
If a valid inference chain yields FALSE, the
premises are unsatisfiable.
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Pargram project

• Large-scale LFG grammars for several languages
• English, German, Japanese (Korean), French,
  Norwegian, Chinese, Turkish, Arabic, Hungarian
• Cover real uses of language--newspapers,
  documents, etc.
• Parallelism test LFG universality claims
• Common c- to f-structure mapping conventions
• (unless typologically motivated variation)
• Invariant underlying f-structures
• Permits shared disambiguation properties, Glue
  interpretation premises
• All grammars run on PARC software (XLE)
• International consortium of linguists
• PARC, Stuttgart, Fuji Xerox, Konstanz, Bergen,
  Sabanci, Oxford, Oman
• Sustained effort--full-week meetings twice a
  year10 years!
• Contributions to linguistics and computational
  linguistics books and papers
• Each group is self-funded, self-managed

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History

• Started in 1994
• English (PARC)
• French (XRCE, now PARC)
• German (IMS-Stuttgart)
• Biannual meetings
• Alternating between Palo Alto and Europe/Japan
• 1998 Japanese started (Fuji Xerox)
• 1999 Norwegian started (University of Bergen)
• 2000 Urdu (Konstanz)
• 2002 Danish started (Copenhagen)
• 2003 Korean (PARC) porting experiment
• 2004 Welsh, Malagasy (Essex, Oxford) Chinese
  (PARC)
• 2005 Arabic (Oman), Turkish (Sabanci), Hungarian

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Goals

• Practical
• Create a capability/platform for NL applications
• translation, information retrieval, ...
• Develop discipline of grammar engineering
• what tools, techniques, conventions make it easy
  to develop and maintain broad-coverage grammars?
• how long does it take?
• how much does it cost?
• Theoretical
• Refine and guide LFG theory through broad
  coverage of multiple languages
• Refine and guide the algorithms and
  implementation (XLE)

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Parallel f-structures (where possible)
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but different c-structures
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Pargram grammars
Rules 251 388 180 56
States 3,239 13,655 1,747 368
Disjuncts 13,294 55,725 12,188 2,012

• German
• English
• French
• Japanese (Korean)

English allows for shallow markup labeled
bracketing, named-entities
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Engineering results

• Grammars and Lexicons
• Parallel f-structures across languages
• Grammar writers cookbook
• New practical formal devices
• Complex categories for efficiency NPnom
  vs. NP (? CASE) NOM
• Optimality marks for robustness
• enlarge grammar without being overrun by
  peculiar analyses
• Lexical priority merging different lexicons

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Theoretical results

• New theory of agreement features
• Separate representation of morphosyntactic
  features
• Phonology-syntax interface
• New analysis of nonconstituent coordination
• Distribution instead of generalization over sets

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XLE Demo
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