Distributional Identification of Non-Referential Pronouns
Published 1 June 2008
Shane Bergsma, Dekang Lin, Randy Goebel
Citations36
Generate an AI Snapshot to get a quick, structured summary of this paper.
Study Snapshot
ObjectiveStudy objective
MethodsResearch methodology
PopulationPopulation studied
Sample sizeSample sizes
OutcomesStudy outcomes here
ResultsStudy results comes here
LimitationsResearch study limitations comes here
A concise AI-generated summary of the paper will appear here once you click Generate AI Snapshot.
TL;DR
An automatic approach to determining whether a pronoun in text refers to a preceding noun phrase or is instead nonreferential, which achieves the highest performance yet attained on this important task.
Abstract
We present an automatic approach to determining whether a pronoun in text refers to a preceding noun phrase or is instead nonreferential. We extract the surrounding textual context of the pronoun and gather, from a large corpus, the distribution of words that occur within that context. We learn to reliably classify these distributions as representing either referential or non-referential pronoun instances. Despite its simplicity, experimental results on classifying the English pronoun it show the system achieves the highest performance yet attained on this important task. 1
Keywords
Computer Science
Elsevier eBooksData Mining: Practical Machine Learning Tools and Techniques
25,718 Citations2011Ian H. Witten, Eibe Frank
Program electronic library and information systemsAn algorithm for suffix stripping
8,136 Citations1980Martin Porter
An algorithm for suffix stripping is described, which has been implemented as a short, fast program in BCPL, and performs slightly better than a much more elaborate system with which it has been compared.
Speech and language processing
3,589 Citations2010Dan Jurafsky, James Martin +1 more
It is now clear that HAL’s creator, Arthur C. Clarke, was a little optimistic in predicting when an artificial agent such as HAL would be avail-able.
Computational LinguisticsA maximum entropy approach to natural language processing
3,120 Citations1996Adam Berger, Vincent J. Della Pietra +1 more
A maximum-likelihood approach for automatically constructing maximum entropy models is presented and how to implement this approach efficiently is described, using as examples several problems in natural language processing.
Europarl: A Parallel Corpus for Statistical Machine Translation
3,106 Citations2005Philipp Koehn
A corpus of parallel text in 11 languages from the proceedings of the European Parliament is collected and its acquisition and application as training data for statistical machine translation (SMT) is focused on.
Automatic retrieval and clustering of similar words
1,555 Citations1998Dekang Lin
A word similarity measure based on the distributional pattern of words allows the automatically constructed thesaurus to be significantly closer to WordNet than Roget Thesaurus is.
Computational LinguisticsAn algorithm for pronominal anaphora resolution
758 Citations1994Shalom Lappin, Herbert J. Leass
The algorithm applies to the syntactic representations generated by McCord's Slot Grammar parser and relies on salience measures derived from syntactic structure and a simple dynamic model of attentional state and to models of anaphora resolution that invoke a variety of informational factors in ranking antecedent candidates.
LinguaResolving pronoun references
615 Citations1978Jerry R. Hobbs
It is shown in a detailed treatment of several examples how semantic analysis locates the antecedents of most pronouns as a by-product in a comprehensive system for semantic analysis of English texts.
Text, speech and language technologyDependency-Based Evaluation of Minipar
606 Citations2003Dekang Lin
A dependency-based method for parser evaluation is presented and a broad-coverage parser, called MINIPAR, is evaluated with the SUSANNE corpus.
Noun classification from predicate-argument structures
543 Citations1990Donald Hindle
The resulting quasi-semantic classification of nouns demonstrates the plausibility of the distributional hypothesis, and has potential application to a variety of tasks, including automatic indexing, resolving nominal compounds, and determining the scope of modification.
Natural Language EngineeringDiscovery of inference rules for question-answering
532 Citations2001Dekang Lin, Patrick Pantel
This paper presents an unsupervised algorithm for discovering inference rules from text based on an extended version of Harris’ Distributional Hypothesis, which states that words that occurred in the same contexts tend to be similar.
Identifying anaphoric and non-anaphoric noun phrases to improve coreference resolution
158 Citations2002Vincent Ng, Claire Cardie
A supervised learning approach to identification of anaphoric and non-anaphoric noun phrases is presented and it is shown how such information can be incorporated into a coreference resolution system that outperforms the best M UC-6 and MUC-7 coreferenceresolution systems on the corresponding MUC coreference data sets.
Distributional Structure
155 Citations1981Zellig S. Harris
Lecture notes in computer scienceAnaphora in Natural Language Understanding: A Survey
146 Citations1981Graeme Hirst
This thesis is an extensive review of the reference and anaphor problem, and the approaches to it that NLU systems have taken, from early systems such as STUDENT through to current discourse-oriented ones such as PAL.
Meeting of the Association for Computational LinguisticsUnsupervised Coreference Resolution in a Nonparametric Bayesian Model
135 Citations2007Aria Haghighi, Dan Klein
An unsupervised, nonparametric Bayesian approach to coreference resolution which models both global entity identity across a corpus as well as the sequential anaphoric structure within each document is presented.
Bootstrapping path-based pronoun resolution
131 Citations2006Shane Bergsma, Dekang Lin
This work learns the likelihood of coreference between a pronoun and a candidate noun based on the path in the parse tree between the two entities, and robustly addresses traditional syntactic coreference constraints.
Automatic processing of large corpora for the resolution of anaphora references
111 Citations1990Ido Dagan, Alon Itai
This paper presents an automatic scheme for collecting statistics on cooccurrence patterns in a large corpus that reflect semantic constraints and thus provide a basis for a useful disambiguation tool.
ScopusIdentification and Resolution of Chinese Zero Pronouns: A Machine Learning Approach
98 Citations2007Shanheng Zhao, Hwee Tou Ng
This work is the first to perform both identification and resolution of Chinese anaphoric zero pronouns using a machine learning approach, with two sets of easily computable features.
Journal of SemanticsDialogue Acts, Synchronizing Units, and Anaphora Resolution
91 Citations2000Miriam Eckert, Michael Strube
The main finding of the corpus analysis is that less than half the pronouns and demonstratives have NP antecedents in the preceding text; 22% have sentential antecesents and the remainder have no identifiable linguistic antecedent.
Literary and Linguistic ComputingApplying machine learning toward an automatic classification of It
87 Citations2001Richard Evans
After a survey of previous treatments of the pronoun it in the literature, some features of instances of it' are proposed that can be used in a novel memory-based learning method to automatically classify those instances.
Computer Speech & LanguageTowards the automatic recognition of anaphoric features in English text: the impersonal pronoun “it”
77 Citations1987Chris D. Paice, G.D. Husk
Research into the automatic recognition of anaphoric features in English is illustrated by an examination of the pronoun “ it”, and simple surface rules are proposed for identifying non-referential usages of “it”.
ACM SIGIR ForumThe DARPA TIPSTER project
65 Citations1992Donna Harman
This note is the first of four papers in this issue describing the ongoing work connected with the DARPA TIPSTER Project, and the next papers by three of the contractors involved in the project provide some details on the systems involved, and some of the initial results.
Resolving It, This, and That in Unrestricted Multi-Party Dialog
46 Citations2007Christoph Müller
The system handles NP-anaphoric as well as discoursedeictic anaphors, i.e. pronouns with VP antecedents, and shows that the system performs significantly better than a recency-based baseline.
Automatic Detection of Nonreferential It in Spoken Multi-Party Dialog
34 Citations2006Christoph Müller
An implemented machine learning system for the automatic detection of nonreferential it in spoken dialog builds on shallow features extracted from dialog transcripts and is usable as a preprocessing filter for a coreference resolution system.
An expectation maximization approach to pronoun resolution
33 Citations2005Colin Cherry, Shane Bergsma
The results indicate that a probabilistic gender/number model, determined automatically from unlabeled text, is a powerful feature for this task.
Identifying Non-Referential It: A Machine Learning Approach Incorporating Linguistically Motivated Patterns
29 Citations2005Adriane Boyd
Disambiguating between generic and referential<i>"you"</i>in dialog
17 Citations2007Surabhi Gupta, Matthew Purver +1 more
An algorithm for a novel task: disambiguating the pronoun you in conversation, which achieves 84% accuracy in two- person conversations and shows promising performance even on more complex multi-party meetings.