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Martin Kay

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Martin Kay CL Introduction 13. Nondeterminism ... Martin Kay CL Introduction 17. Unification. Attribute Report 1 Report 2 Combined Report ... – PowerPoint PPT presentation

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Title: Martin Kay


1
Ling 138/238
Introduction to
Computational Linguistics
  • Martin Kay
  • Stanford University

2
  • 30 Introduction
  • Oct 1 Complexity String search
  • 6 Knuth-Morris-Pratt Boyer Moore
  • 8 Suffix Trees
  • 13 Tagging Alignment
  • 15
  • 20 Chomsky Hierarchy Regular Expressions
  • 22
  • 27 Finite-state automata
  • 39

3
  • Nov 3 Morphology
  • 5
  • 10 Context-free grammar
  • 12
  • 17 Unification, HPSG, LFG
  • 19
  • 24 Machine Translation
  • 26
  • Dec 1 Summary Wrap-up
  • 3

4
Linguistics 138/238
  • Martin Kay
  • KAY_at_csli.stanford.edu
  • 740 3043
  • Margaret Jacks 124
  • Office hours TuTh 4.15-5.45 p.m.

5
Prerequisites and Expectations
  • No prerequisites
  • Classroom participation
  • Occasional readings
  • Learn Prolog
  • Laboratory sessions
  • Homework Problems
  • Project

6
Project
  • Learn something new about language
  • Significant programming
  • Group work
  • Modifying or amplifying existing code

A HMM-based tagger A searcher for tagged
text Implementation of Suffix trees Morphological
analysis Named-entity recognition
7
Intellectual Relations
  • Relation to
  • Linguistics
  • Psychology
  • Artificial Intelligence
  • Computer Science

Abstract
Process
8
Computational Linguistics as Science
Computing
as
Inspiration
9
Ideas from Computing
  • Search
  • Divide and Conquer
  • Guides and Oracles
  • Nondeterminism
  • Dynamic Programming
  • Scheduling, agendas
  • Compilation
  • Unification
  • Automata Theory
  • Co-routining and parallelism
  • Top-down vs. bottom-up
  • Complexity

10
Ideas from Computing
  • Search
  • Nondeterminism
  • Dynamic Programming

11
A Maize
Search Nondeterminism Dynamic Programming
Keep you right hand on the wall
12
A Maize
Search Nondeterminism Dynamic Programming
13
Nondeterminism
Search Nondeterminism Dynamic Programming
  • A process is nondeterministic if there are points
    in it when a choice must be made, but the
    information necessary to make the choice is not
    available.
  • Solution Pick one of the alternatives. If it
    does not work out, come back and pick another
    one.
  • Note the information required to make the choice
    was available after all!

14
DynamicProgramming
Search Nondeterminism Dynamic Programming
Chalons
Metz
192
266
161
Paris
Strasbourg
458
619
288
234
115
620
344
Mulhouse
276
Dijon
15
The CKY Chart
Search Nondeterminism Dynamic Programming
people np np np s s s like prep pp p
p v vp vp the det np np French adj n
n n drink n vp
Context free All phrase with the same
Coverage, and Category enter into larger
phrases as a single item
16
Ideas from Computing
  • Unification

17
Unification
Unification
  • Attribute Report 1 Report 2 Combined Report
  • eyes blue blue blue
  • hair black or brown brown or red brown
  • accent Italian Italian
  • wife see below see below see below
  • children Ahemed Angela Rebecca Angela Ahmed,
    Angela
  • Rebecca
  • age middle 48 Middle
  • Wife
  • eyes brown brown
  • weight 247 lbs 112 Kg 247 lbs
  • disposition surly surly

18
Unification
Unification
  • Attribute Report 1 Report 2 Combined Report
  • eyes blue blue blue
  • hair black or brown brown or red brown
  • accent Italian Italian
  • wife see below see below see below
  • children Ahemed Angela Rebecca Angela Ahmed,
    Angela
  • Rebecca
  • age middle 48 Middle
  • Wife
  • eyes brown grey FAIL
  • weight 247 lbs 112 Kg 247 lbs
  • disposition surly surly

19
English Agreement
Unification
  • The dog sleeps
  • The dogs sleep
  • The dog slept
  • The dogs slept
  • The sheep sleeps
  • The sheep sleep
  • The sheep slept
  • The sheep that was in the barn slept
  • The sheep that were in the barn slept

20
German Case
Unification
  • Der Junge sah den Lehrer
  • Den Lehrer sah der Junge
  • Das Mädchen sah der Junge
  • der Junge sah das Mädchen
  • Die Lehrerin sah den Lehrer
  • Die Lehrerin sah das Mädchen

21
Ideas from Computing
  • Finite-State Methods

22
Finite-State Methods in Language Processing
Finite-State Methods
  • The Application of a branch of mathematics
  • The regular branch of automata theory
  • to a branch of computational linguistics in which
    what is crucial is (or can be reduced to)
  • Properties of string sets and string relations
    with
  • A notion of bounded dependency

23
Applications
Finite-State Methods
  • Finite Languges
  • Dictionaries
  • Compression
  • Phenomena involving bounded dependency
  • Morpholgy
  • Spelling
  • Hyphenation
  • Tokenization
  • Morphological Analysis
  • Phonology
  • Approximations to phenomena involving mostly
    bounded dependency
  • Syntax
  • Phenomena that can be translated into the realm
    of strings with bounded dependency
  • Syntax

24
Ideas from Computing
  • Complexity

25
The Chomsky Hierarchy
Complexity
Grammar Language Automaton Type 0 Recursively
Turing Machines Enumerable
Sets Context-sensitive Context-sensitive Nondeter
ministic linear space bound Turing
Machines Context-free Context-free Nondeterminist
ic push- down automata LR(k) Deterministic
Context- Deterministic push-down free
automata Regular Expressions Regular
Sets Finite-state automata Left (Right) Linear
26
Computation and Psychology
  • Sentence Processing

27
Computational Linguistics as Engineering
Computing
as
Power
28
Tools for Linguists
  • TLF, OED
  • Corpus Linguistics
  • Field Notes
  • Grammar Testing

29
Translation
  • MT, Translator's Tools
  • Alignment, Dictionaries, Term Banks
  • Normalization and Tuning

30
Other Applications
  • Writer's Tools
  • Spelling
  • Dictionary, Thesaurus
  • Grammar
  • Natural Language Interfaces
  • Information Storage and Retrieval

31
CL AI
  • Text, Meaning, and Interpretation

Linguistics
???



Text
Interpretation
Meaning
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