left corner parsing parsing tricks
play

Left-Corner Parsing Parsing Tricks Technique for 1 word of - PDF document

Feb 20, 2024 •237 likes •304 views

Left-Corner Parsing Parsing Tricks Technique for 1 word of lookahead in algorithms like Earleys (can also do multi-word lookahead but its harder) 600.465 - Intro to NLP - J. Eisner 1 600.465 - Intro to NLP - J. Eisner 2 Basic

  1. Left-Corner Parsing Parsing Tricks � Technique for 1 word of lookahead in algorithms like Earley’s � (can also do multi-word lookahead but it’s harder) 600.465 - Intro to NLP - J. Eisner 1 600.465 - Intro to NLP - J. Eisner 2 Basic Earley’s Algorithm 0 Papa 1 0 Papa 1 0 ROOT . S 0 NP Papa . attach 0 ROOT . S 0 NP Papa . predict 0 S . NP VP 0 S NP . VP 0 S . NP VP 0 S NP . VP 0 NP . Det N 0 NP NP . PP 0 NP . Det N 0 NP NP . PP 0 NP . NP PP 0 NP . NP PP 1 VP . V NP 0 NP . Papa 0 NP . Papa 1 VP . VP PP 0 Det . the 0 Det . the 0 Det . a 0 Det . a 0 Papa 1 0 Papa 1 0 ROOT . S 0 NP Papa . 0 ROOT . S 0 NP Papa . 0 S . NP VP 0 S NP . VP 0 S . NP VP 0 S NP . VP 0 NP . Det N 0 NP NP . PP predict 0 NP . Det N 0 NP NP . PP 0 NP . NP PP 1 VP . V NP 0 NP . NP PP 1 VP . V NP predict 0 NP . Papa 1 VP . VP PP 0 NP . Papa 1 VP . VP PP 0 Det . the 1 PP . P NP 0 Det . the 1 PP . P NP � .V makes us add all the verbs in the 0 Det . a 0 Det . a 1 V . ate vocabulary! � Slow – we’d like a shortcut. 1 V . drank 1 V . snorted 1

  2. 0 Papa 1 0 Papa 1 0 ROOT . S 0 NP Papa . 0 ROOT . S 0 NP Papa . 0 S . NP VP 0 S NP . VP 0 S . NP VP 0 S NP . VP 0 NP . Det N 0 NP NP . PP 0 NP . Det N 0 NP NP . PP 0 NP . NP PP 1 VP . V NP 0 NP . NP PP 1 VP . V NP predict 0 NP . Papa 1 VP . VP PP 0 NP . Papa 1 VP . VP PP predict 0 Det . the 1 PP . P NP 0 Det . the 1 PP . P NP � Every .VP adds all VP � … rules again. � .P makes us add all the prepositions … 0 Det . a 1 V . ate � Before adding a rule, check it’s not a 0 Det . a 1 V . ate 1 V . drank 1 V . drank duplicate. � Slow if there are > 700 VP � … rules, 1 V . snorted 1 V . snorted so what will you do in Homework 3? 1 P . with 1-word lookahead w ould help 1-word lookahead w ould help 0 Papa 1 ate 0 Papa 1 ate 0 ROOT . S 0 NP Papa . 0 ROOT . S 0 NP Papa . 0 S . NP VP 0 S NP . VP 0 S . NP VP 0 S NP . VP 0 NP . Det N 0 NP NP . PP 0 NP . Det N 0 NP NP . PP 0 NP . NP PP 1 VP . V NP 0 NP . NP PP 1 VP . V NP In fact, no point in adding any constituent 0 NP . Papa 1 VP . VP PP 0 NP . Papa 1 VP . VP PP that can’t start with ate 0 Det . the 1 PP . P NP 0 Det . the 1 PP . P NP Don’t bother adding PP, P, etc. 0 Det . a 1 V . ate 0 Det . a 1 V . ate 1 V . drank 1 V . drank 1 V . snorted 1 V . snorted No point in adding words other than ate No point in adding words other than ate 1 P . with 1 P . with With Left-Corner Filter 0 Papa 1 ate 0 Papa 1 ate 0 ROOT . S 0 NP Papa . attach 0 ROOT . S 0 NP Papa . 0 S . NP VP 0 S NP . VP 0 S . NP VP 0 S NP . VP predict 0 NP . Det N 0 NP NP . PP 0 NP . Det N 0 NP NP . PP PP can’t start with ate 0 NP . NP PP 0 NP . NP PP 1 VP . V NP 0 NP . Papa 0 NP . Papa 1 VP . VP PP Birth control – now we won’t predict 0 Det . the 0 Det . the 1 PP . P NP 0 Det . a 0 Det . a 1 PP . ate either! Need to know that ate can’t start PP Take closure of all categories that it does start … 2

  3. 0 Papa 1 ate 0 Papa 1 ate 0 ROOT . S 0 NP Papa . 0 ROOT . S 0 NP Papa . 0 S . NP VP 0 S NP . VP 0 S . NP VP 0 S NP . VP 0 NP . Det N 0 NP NP . PP 0 NP . Det N 0 NP NP . PP predict 0 NP . NP PP 1 VP . V NP 0 NP . NP PP 1 VP . V NP predict 0 NP . Papa 1 VP . VP PP 0 NP . Papa 1 VP . VP PP 0 Det . the 1 V . ate 0 Det . the 1 V . ate 0 Det . a 1 V . drank 0 Det . a 1 V . drank 1 V . snorted 1 V . snorted Merging Right-Hand Sides Merging Right-Hand Sides � Similarly, grammar might have rules � Grammar might have rules X ? X ? A G H P A G H P X ? X ? B G H P A G H Q � Could end up with both of these in chart: � Could end up with both of these in chart: ( 2, X ? A . G H P) in column 5 ( 2, X ? A . G H P) in column 5 ( 2, X ? B . G H P) in column 5 ( 2, X ? A . G H Q) in column 5 � But these are now interchangeable: if one � Not interchangeable, but we’ll be processing produces X then so will the other them in parallel for a while … � To avoid this redundancy, can always use � Solution: write grammar as X ? A G H (P| Q) dotted rules of this form: X ? ... G H P 600.465 - Intro to NLP - J. Eisner 15 600.465 - Intro to NLP - J. Eisner 16 Merging Right-Hand Sides Merging Right-Hand Sides X ? ( A | B) G H (P | Q) � Combining the two previous cases: NP ? ( Det | ? ) Adj * N X ? A G H P � These are regular expressions! X ? A G H Q � Build their minimal DFAs: X ? B G H P X ? A P B G H Q X ? becomes G H B Q X ? ( A | B) G H (P | Q) Adj � And often nice to write stuff like � Automaton states Det NP ? NP ? ( Det | ? ) Adj * N replace dotted N rules ( X ? Adj A G . H P ) N 600.465 - Intro to NLP - J. Eisner 17 600.465 - Intro to NLP - J. Eisner 18 3

  4. Merging Right-Hand Sides Merging Right-Hand Sides Indeed, all NP ? rules can be unioned into a single DFA! Indeed, all NP ? rules can be unioned into a single DFA! NP ? NP ? ADJP ADJP JJ JJ NN NNS ADJP ADJP JJ JJ NN NNS ADJP NP ? ADJP DT NN | ADJP DT NN NP ? ADJP JJ NN | ADJP JJ NN NP ? NP ? ADJP JJ NN NNS | ADJP JJ NN NNS DT NP ? ADJP JJ NNS | ADJP JJ NNS NP ? ADJP NN | ADJP NN DFA NP ? ADJP NN NN | ADJP NN NN NP NP ? regular ADJP NN NNS | ADJP NN NNS NP ? ADJP NNS | ADJP NNS expression NP ? ADJP NPR | ADJP NPR NP ? ADJP NPRS | ADJP NPRS NP ? DT | DT ADJ NP ? DT ADJP | DT ADJP NP ? ADJP ? DT ADJP , JJ NN | DT ADJP , JJ NN NP ? P DT ADJP ADJP NN | DT ADJP ADJP NN NP ? DT ADJP JJ JJ NN | DT ADJP JJ JJ NN NP ? DT ADJP JJ NN | DT ADJP JJ NN NP ? DT ADJP JJ NN NN | DT ADJP JJ NN NN ADJP etc. etc. 600.465 - Intro to NLP - J. Eisner 19 600.465 - Intro to NLP - J. Eisner 20 Earley’s Algorithm on DFAs Earley’s Algorithm on DFAs � What does Earley ’s algorithm now look like? � What does Earley ’s algorithm now look like? PP PP … … Adj PP VP ? VP ? Det … … NP ? NP NP N Adj PP ? … N Column 4 Column 4 … … (2, ) predict (2, ) predict (4, ) (4, ) 600.465 - Intro to NLP - J. Eisner 21 600.465 - Intro to NLP - J. Eisner 22 Earley’s Algorithm on DFAs Earley’s Algorithm on DFAs � What does Earley ’s algorithm now look like? � What does Earley ’s algorithm now look like? PP PP … … Adj PP Adj PP VP ? VP ? Det Det … … NP ? NP ? NP NP N N Adj Adj PP ? … PP ? … N N Column 4 Column 5 … Column 7 Column 4 Column 5 … Column 7 … … … … predict predict (2, ) (4, ) (2, ) (4, ) or attach? or attach? (4, ) (4, ) (7, ) Both! (4, ) (4, ) (4, ) (4, ) (2, ) 600.465 - Intro to NLP - J. Eisner 23 600.465 - Intro to NLP - J. Eisner 24 4

Recommend

Left-corner parsing Laura Kassner laura.kassner@gmx.de Computational Linguistics II: Parsing

Left-corner parsing Laura Kassner laura.kassner@gmx.de Computational Linguistics II: Parsing

Left-corner parsing Laura Kassner laura.kassner@gmx.de Computational Linguistics II: Parsing January 10th, 2007 Left-corner parsing Basics Building a left-corner recognizer... ... and transforming it into a parser Comparison to

4.09k views • 190 slides
Models of Human Parsing Experimental Data 2 Informatics 2A: Lecture 22 Eye-tracking Reading

Models of Human Parsing Experimental Data 2 Informatics 2A: Lecture 22 Eye-tracking Reading

Human Parsing Human Parsing Experimental Data Experimental Data Bottom-Up Parser Bottom-Up Parser Left Corner Parser Left Corner Parser Human Parsing 1 Cognitive Constraints Garden Paths Dimensions of Parsing Models of Human Parsing

537 views • 9 slides
Computational Linguistics II: Parsing Left-corner-Parsing Frank Richter & Jan-Philipp S

Computational Linguistics II: Parsing Left-corner-Parsing Frank Richter & Jan-Philipp S

Computational Linguistics II: Parsing Left-corner-Parsing Frank Richter & Jan-Philipp S ohn fr@sfs.uni-tuebingen.de, jp.soehn@uni-tuebingen.de January 15th, 2007 Richter/S ohn (WS 2006/07) Computational Linguistics II: Parsing

648 views • 29 slides
Bottom Up Parsing Also known as Shift-Reduce parsing More powerful than top down Dont

Bottom Up Parsing Also known as Shift-Reduce parsing More powerful than top down Dont

9/26/2012 Bottom Up Parsing Also known as Shift-Reduce parsing More powerful than top down Dont need left factored grammars Can handle left recursion Bottom Up Parsing Attempt to construct parse tree from an input string

654 views • 6 slides
Using Left-corner Parsing to Encode Universal Structural Constraints in Grammar Induction

Using Left-corner Parsing to Encode Universal Structural Constraints in Grammar Induction

Using Left-corner Parsing to Encode Universal Structural Constraints in Grammar Induction Hiroshi Noji Yusuke Miyao Mark Johnson Nara Institute of National Institute of Macquarie University Science and Technology Informatics 1

565 views • 21 slides
Plan for Today Predictive parsing as a specific subclass of recursive descent parsing

Plan for Today Predictive parsing as a specific subclass of recursive descent parsing

Plan for Today Predictive parsing as a specific subclass of recursive descent parsing complexity comparisons with general parsing might have to left-factor necessary to remove left-recursion (MiniSVG modification as example) Working

346 views • 5 slides
CSC 4181 Compiler Construction Parsing 1 1 Outline Top-down v.s. Bottom-up Top-down parsing

CSC 4181 Compiler Construction Parsing 1 1 Outline Top-down v.s. Bottom-up Top-down parsing

CSC 4181 Compiler Construction Parsing 1 1 Outline Top-down v.s. Bottom-up Top-down parsing Bottom-up parsing Recursive-descent Shift-reduce parsers parsing LR(0) parsing LL(1) parsing LR(0) items LL(1) parsing

429 views • 29 slides
Introduction to Bottom-Up Parsing Shift-reduce parsing The LR parsing algorithm

Introduction to Bottom-Up Parsing Shift-reduce parsing The LR parsing algorithm

Outline Review LL parsing Introduction to Bottom-Up Parsing Shift-reduce parsing The LR parsing algorithm Constructing LR parsing tables 2 Top-Down Parsing: Review Top-Down Parsing: Review Top-down parsing expands a

470 views • 13 slides
Lectures 7 and 8. Parsing (syntax analysis) Wei Le 2015.9 Bottom Up Parsing Recognize many

Lectures 7 and 8. Parsing (syntax analysis) Wei Le 2015.9 Bottom Up Parsing Recognize many

Lectures 7 and 8. Parsing (syntax analysis) Wei Le 2015.9 Bottom Up Parsing Recognize many programming languages, used in practice More general, more powerful parser: less restrictions on grammars, e.g., can handle left-recursive grammar

680 views • 64 slides
Computational Linguistics II: Parsing Overview, Left-Recursion, Bottom-up Parsing Frank Richter

Computational Linguistics II: Parsing Overview, Left-Recursion, Bottom-up Parsing Frank Richter

Computational Linguistics II: Parsing Overview, Left-Recursion, Bottom-up Parsing Frank Richter & Jan-Philipp S ohn fr@sfs.uni-tuebingen.de, jp.soehn@uni-tuebingen.de Computational Linguistics II: Parsing p.1 The Big Picture

667 views • 43 slides
Plan for Today Recall Predictive Parsing when it works and when it doesnt necessary to

Plan for Today Recall Predictive Parsing when it works and when it doesnt necessary to

Plan for Today Recall Predictive Parsing when it works and when it doesnt necessary to remove left-recursion might have to left-factor Error recovery for predictive parsers Predictive parsing as a specific subclass of recursive

590 views • 10 slides
Top-Down Parsing Slides modified from Louden Book and Dr. Scherger Top Down Parsing A

Top-Down Parsing Slides modified from Louden Book and Dr. Scherger Top Down Parsing A

Compiler Design and Construction Top-Down Parsing Slides modified from Louden Book and Dr. Scherger Top Down Parsing A top-down parsing algorithm parses an input string of tokens by tracing out the steps in a leftmost derivation. Such an

1.12k views • 96 slides
Statistical Dependency Parsing in Korean: From Corpus Generation To Automatic Parsing Workshop on

Statistical Dependency Parsing in Korean: From Corpus Generation To Automatic Parsing Workshop on

Statistical Dependency Parsing in Korean: From Corpus Generation To Automatic Parsing Workshop on Statistical Parsing of Morphologically-Rich Languages 12th International Conference on Parsing Technologies Jinho D. Choi & Martha Palmer

199 views • 19 slides
Basic Parsing Algorithms Chart Parsing Seminar Recent Advances in Parsing Technology WS

Basic Parsing Algorithms Chart Parsing Seminar Recent Advances in Parsing Technology WS

Basic Parsing Algorithms Chart Parsing Seminar Recent Advances in Parsing Technology WS 2011/2012 Anna Schmidt Talk Outline Chart Parsing Basics Chart Parsing Algorithms Earley Algorithm CKY Algorithm Basics

1.12k views • 73 slides
Overview Introduction Lexicalized TAG, Advantages of parsing with LTAG Parsing LTAGs

Overview Introduction Lexicalized TAG, Advantages of parsing with LTAG Parsing LTAGs

Parsing with Lexicalized TAG (1) Extracting and comparing LTAG (2) Presentation by Philip John Gorinski Seminar Recent Advances in Parsing Technology Saarland University, Winter Term 2011/12 (1) Yves Shabes, Aravind K. Joshi, 1990 (2)

514 views • 36 slides
* 07/16/96 Plan for Today Shift-reduce parsing The problem with predictive top down parsing

* 07/16/96 Plan for Today Shift-reduce parsing The problem with predictive top down parsing

* 07/16/96 Plan for Today Shift-reduce parsing The problem with predictive top down parsing CS453 : Shift Reduce Parsing LR parsing: bottom up Unambiguous Grammars LR(0) and SLR Parse Tables Performs a right-most derivation in

316 views • 6 slides
CS453 : JavaCUP and error recovery CS453 Shift-reduce Parsing 1 Shift-reduce parsing in an LR

CS453 : JavaCUP and error recovery CS453 Shift-reduce Parsing 1 Shift-reduce parsing in an LR

CS453 : JavaCUP and error recovery CS453 Shift-reduce Parsing 1 Shift-reduce parsing in an LR parser LR(k) parser Left-to-right parse Right-most derivation K-token look ahead LR parsing algorithm using an LR parse table

591 views • 9 slides
1 Determinism and Parsing The parsing problem is, given a string w and a context-free grammar G ,

1 Determinism and Parsing The parsing problem is, given a string w and a context-free grammar G ,

1 Determinism and Parsing The parsing problem is, given a string w and a context-free grammar G , to decide if w L ( G ), and if so, to construct a derivation or a parse tree for w . Parsing is studied in courses in compilers. To be efficient

519 views • 12 slides
Bottom-up parsing LR parsing Construct parse tree for input from leaves up LR( k ) parsing

Bottom-up parsing LR parsing Construct parse tree for input from leaves up LR( k ) parsing

Bottom-up parsing LR parsing Construct parse tree for input from leaves up LR( k ) parsing reducing a string of tokens to single start symbol L eft-to-right scan of input, R ightmost derivation (inverse of deriving a string of tokens from

413 views • 5 slides
Dependency Parsing & Feature-based Parsing Ling571 Deep Processing Techniques for NLP

Dependency Parsing & Feature-based Parsing Ling571 Deep Processing Techniques for NLP

Dependency Parsing & Feature-based Parsing Ling571 Deep Processing Techniques for NLP February 2, 2015 Roadmap Dependency parsing Graph-based dependency parsing Maximum spanning tree CLE Algorithm Learning

899 views • 87 slides
Statistical Parsing Parsing context-free languages ar ltekin University of Tbingen

Statistical Parsing Parsing context-free languages ar ltekin University of Tbingen

Statistical Parsing Parsing context-free languages ar ltekin University of Tbingen Seminar fr Sprachwissenschaft November 8, 2016 Recap Parsing basics CKY Earley Closing Ingredients of a (natural language) parser .

1.17k views • 51 slides
Generalised Parsing and Combinator Parsing A Happy Marriage? L. Thomas van Binsbergen

Generalised Parsing and Combinator Parsing A Happy Marriage? L. Thomas van Binsbergen

Conventional Parser Combinators Aspects of Generalised Parsing Combinators for Generalised Parsing Generalised Parsing and Combinator Parsing A Happy Marriage? L. Thomas van Binsbergen ltvanbinsbergen@acm.org Royal Holloway, University of

452 views • 30 slides
Robust Incremental Neural Semantic Graph Parsing Jan Buys and Phil Blunsom Dependency Parsing vs

Robust Incremental Neural Semantic Graph Parsing Jan Buys and Phil Blunsom Dependency Parsing vs

Robust Incremental Neural Semantic Graph Parsing Jan Buys and Phil Blunsom Dependency Parsing vs Semantic Parsing Dependency parsing models the syntactic structure between words in a sentence. Dependency Parsing vs Semantic Parsing

637 views • 31 slides
Statistical Parsing Dependency parsing ar ltekin University of Tbingen Seminar fr

Statistical Parsing Dependency parsing ar ltekin University of Tbingen Seminar fr

Statistical Parsing Dependency parsing ar ltekin University of Tbingen Seminar fr Sprachwissenschaft November 2016 Recap/background Dependency grammar Dependency parsing Evaluation Summary Ingredients of a parser

1.44k views • 89 slides

More recommend