Dependency Parsing CMSC 723 / LING 723 / INST 725 M ARINE C ARPUAT - PowerPoint PPT Presentation

Jan 11, 2024 •531 likes •856 views

Dependency Parsing CMSC 723 / LING 723 / INST 725 M ARINE C ARPUAT marine@cs.umd.edu Slides credit: Joakim Nivre & Ryan McDonald Agenda Formalizing dependency graphs Formalizing transition-based parsing Graph-based

Dependency Parsing CMSC 723 / LING 723 / INST 725 M ARINE C ARPUAT marine@cs.umd.edu Slides credit: Joakim Nivre & Ryan McDonald
Agenda • Formalizing dependency graphs • Formalizing transition-based parsing – Graph-based – Transition-based most material based on Kubler, McDonald & Nivre
Dependencies Typed: Label indicating relationship between words ● prep pobj dobj nsubj det det I saw a girl with a telescope Untyped: Only which words depend ● I saw a girl with a telescope
Data-driven dependency parsing Goal: learn a good predictor of dependency graphs Input: x Output: dependency graph/tree G Can be framed as a structured prediction task - very large output space - with interdependent labels
FOR ORMA MALIZ IZING ING DE DEPE PENDENC NDENCY Y REPR PRES ESENT ENTATIO TIONS NS
Dependency Graphs
Dependency Graph Notation
Properties of Dependency Trees
Non-Projectivity • Most theoretical frameworks do not assume projectivity • Non-projective structures are needed to represent – Long-distance dependencies – Free word order
GR GRAP APH-BASED BASED PAR ARSING ING
Directed Spanning Trees
Maximum Spanning Tree • Assume we have an arc factored model i.e. weight of graph can be factored as sum or product of weights of its arcs • Chu-Liu-Edmonds algorithm can find the maximum spanning tree for us! – Greedy recursive algorithm – Naïve implementation: O(n^3)
Chu-Liu-Edmonds illustrated
Chu-Liu-Edmonds illustrated
Chu-Liu-Edmonds illustrated
Chu-Liu-Edmonds illustrated
Chu-Liu-Edmonds illustrated
Arc weights as linear classifiers
Example of classifier features
How to score a graph G using features? By definition of arc weights Arc-factored model as linear classifiers assumption
How can we learn the classifier from data?
TR TRAN ANSITIO ITION-BASED BASED DE DEPE PENDENC NDENCY Y PAR ARSE SER
Transition-based parsing
Transition-based parsing
Deterministic parsing with an oracle
Stack-based transition system
Transitions & Preconditions
Let’s try it out…
A few steps illustrated…
A few steps illustrated…

Download Presentation

Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

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

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

Dependency Parsing CMSC 723 / LING 723 / INST 725 Marine Carpuat Fig credits: Joakim Nivre, Dan

Dependency Parsing CMSC 723 / LING 723 / INST 725 Marine Carpuat Fig credits: Joakim Nivre, Dan Jurafsky & James Martin Dependency Parsing Formalizing dependency trees Transition-based dependency parsing Shift-reduce parsing

676 views • 24 slides

Dependency Parsing 2 CMSC 723 / LING 723 / INST 725 Marine Carpuat Fig credits: Joakim Nivre,

Dependency Parsing 2 CMSC 723 / LING 723 / INST 725 Marine Carpuat Fig credits: Joakim Nivre, Dan Jurafsky & James Martin Dependency Parsing Formalizing dependency trees Transition-based dependency parsing Shift-reduce parsing

1.02k views • 52 slides

Natural Language Processing Other Syntactic Models Parsing IV Dan Klein UC Berkeley Dependency

Natural Language Processing Other Syntactic Models Parsing IV Dan Klein UC Berkeley Dependency Parsing Dependency Parsing Pure dependency parsing is only cubic [Eisner 99] Lexicalized parsers can be seen as producing dependency trees

314 views • 5 slides

Last class Dependency parsing and logistic regression Dependency parsing: a fully lexicalized

Last class Dependency parsing and logistic regression Dependency parsing: a fully lexicalized formalism; tree edges connect words in the Shay Cohen sentence based on head-dependent relationships. (based on slides by Sharon Goldwater) a

359 views • 11 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 Semantic Parsing Dependency parsing models the syntactic structure between words in a sentence. Dependency Parsing vs Semantic Parsing

637 views • 31 slides

Dependency Parsing II CMSC 470 Marine Carpuat Graph-based Dependency Parsing Slides credit:

Dependency Parsing II CMSC 470 Marine Carpuat Graph-based Dependency Parsing Slides credit: Joakim Nivre Directed Spanning Trees Dependency Parsing as Finding the Maximum Spanning Tree Views parsing as finding the best directed spanning

981 views • 61 slides

Dependency Grammars and Parsing CMSC 473/673 UMBC Outline Review: PCFGs and CKY Dependency

Dependency Grammars and Parsing CMSC 473/673 UMBC Outline Review: PCFGs and CKY Dependency Grammars Dependency Parsing (Shift-reduce) From syntax to semantics Probabilistic Context Free Grammar 1.0 S NP VP 1.0 PP P NP .4 NP Det

862 views • 75 slides

Algorithms for NLP CS 11-711 Fall 2020 Lecture 14: Graph-based dependency parsing Emma

Algorithms for NLP CS 11-711 Fall 2020 Lecture 14: Graph-based dependency parsing Emma Strubell Announcements No recitation on Friday (Tartan Community Day). 2 Dependency parsing 3 Dependency parsing Input buffer Transition-based

1.15k views • 77 slides

Thoughts on Learner Data and Motivation Learner Language Dependency Parsing and Dependency

Thoughts on Learner Data and Dependency Parsing Niels Ott, Ramon Ziai, Julia Krivanek, Detmar Meurers Introduction and Thoughts on Learner Data and Motivation Learner Language Dependency Parsing and Dependency Annotation Approximated

812 views • 53 slides

Marina Valeeva Outline 2 1. Introduction What is Dependency Parsing? What is a

GRAPH-BASED DEPENDENCY PARSING Marina Valeeva Outline 2 1. Introduction What is Dependency Parsing? What is a Dependency Tree? Projectivity vs. Non-Projectivity 2. Graph-Based Dependency Parsing 3. Models Edge Based Factorization

572 views • 40 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 Parsing of Morphologically-Rich Languages 12th International Conference on Parsing Technologies Jinho D. Choi & Martha Palmer

199 views • 19 slides

Graph-based Dependency Parsing (Chu-Liu-Edmonds algorithm) Sam Thomson (with thanks to Swabha

Graph-based Dependency Parsing (Chu-Liu-Edmonds algorithm) Sam Thomson (with thanks to Swabha Swayamdipta) University of Washington, CSE 490u February 22, 2017 Outline Dependency trees Three main approaches to parsing

648 views • 54 slides

Lecture 19: Dependency Grammars and Dependency Parsing Julia Hockenmaier juliahmr@illinois.edu

CS447: Natural Language Processing http://courses.engr.illinois.edu/cs447 Lecture 19: Dependency Grammars and Dependency Parsing Julia Hockenmaier juliahmr@illinois.edu 3324 Siebel Center Todays lecture Dependency Grammars Dependency

792 views • 54 slides

Dependency Parsing Joakim Nivre Uppsala University Department of Linguistics and Philology

Dependency Parsing Joakim Nivre Uppsala University Department of Linguistics and Philology joakim.nivre@lingfil.uu.se Dependency Parsing 1(14) 1. Dependency Trees 2. Arc-Factored Models 3. Online Learning 4. Eisners Algorithm 5.

726 views • 14 slides

1 Previously, we looked at random tes.ng, or fuzzing, as

{HEADSHOT} Wri.ng and maintaining tests is a tedious and error-prone process. Modern technology has come a long way to help automate parts of

619 views • 50 slides

Updating Directed Minimum Cost Spanning Trees Orestis A. Telelis joint work with Gerasimos G.

Introduction Complexity of Updates A dynamic algorithm Experiments Updating Directed Minimum Cost Spanning Trees Orestis A. Telelis joint work with Gerasimos G. Pollatos Vassilis Zissimopoulos Department of Informatics and

1.03k views • 54 slides

On Approximating Degree- Bounded Network Design Problems Xi a ngyu Guo joint work with Guy

On Approximating Degree- Bounded Network Design Problems Xi a ngyu Guo joint work with Guy Korts a rz, Bundit L a ekh a nukit, Shi Li, D a niel V a z, a nd Ji a yi Xi a n Aug 17, 2020 Network Design Problems Input: an graph c E G

475 views • 34 slides

Graph Layout Maneesh Agrawala CS 448B: Visualization Fall 2017 Last Time: Color 1 Computing

Graph Layout Maneesh Agrawala CS 448B: Visualization Fall 2017 Last Time: Color 1 Computing Cone Response Integrate cone response with input spectra L vs. Luminance, L* Corners of the RGB color cube Luminance values L* values L from

884 views • 49 slides

A Functional Graph Library Based on Inductive Graphs and Functional Graph Algorithms by Martin

A Functional Graph Library Based on Inductive Graphs and Functional Graph Algorithms by Martin Erwig Presentation by Christian Doczkal March 22 nd , 2006 Structure Motivation Inductive graph definition Implementation Binary

467 views • 17 slides

Subnormal weighted shifts on directed trees whose n th powers have trivial domain Zenon Jabo

Problem Solution Proof Subnormal weighted shifts on directed trees whose n th powers have trivial domain Zenon Jabo nski Instytut Matematyki Uniwersytet Jagiello nski joint work with P . Budzy nski, I. B. Jung and J. Stochel OTOA

674 views • 38 slides

Machine Learning 2007: Lecture 4 Instructor: Tim van Erven (Tim.van.Erven@cwi.nl) Website:

Machine Learning 2007: Lecture 4 Instructor: Tim van Erven (Tim.van.Erven@cwi.nl) Website: www.cwi.nl/erven/teaching/0708/ml/ September 27, 2007 1 / 29 Overview Organisational Organisational Matters Matters An Unbiased Hypothesis

968 views • 49 slides

Brauer Trees and Brauer Tree Algebras Adam Wood Department of Mathematics University of Iowa

Brauer Trees and Brauer Tree Algebras Adam Wood Department of Mathematics University of Iowa Bradley University Math Colloquium November 14, 2019 Outline Overview of Representation Theory Brauer Trees Representations of Finite Groups

810 views • 77 slides