Resolution of anaphoric reference is one of the most important challenges in natural language processing (NLP). Functionality of most NLP systems crucially relies on an accurate mechanism for determining which expressions in the input refer to the same entity in the real world. The immense complexity of this issue has led the research community to adopt predominantly knowledge-poor methods, des...

Linking implicit semantic roles is a challeng-ing problem in discourse processing. Unlikeprior work inspired by SRL, we cast this prob-lem as an anaphora resolution task and embedit in an entity-based coreference resolution(CR) architecture. Our experiments clearlyshow that CR-oriented features yield strongestperformance exceeding a strong baseline. Weaddress the...

This paper describes a knowledge-poor anaphora resolution approach based on shallow meaning representation of sentences. Within our representation, we define a new local domain which provides a powerful cue for resolving pronominal anaphora. Other information used included syntactic information, syntactic parallelism and salience weights. We collected 111 singular 3 person pronouns from open do...

We describe three experiments that use priming methodology to investigate the nature of the abstract mental representations activated during pronoun resolution, in order to contribute to our understanding of how structural representations and semantic coherence representations influence pronoun interpretation. The results of Experiment 1 suggest that there exists a level of abstract anaphoric d...

Resolution of the anaphoric entities in natural language text is very much essential to extract the complete information from the text. In this paper, we present a methodology to resolve one of the difficult pronouns, plural pronouns with split antecedents in Tamil. We have used a salience measure based approach with salience factors obtained from sub-categorization information of nouns and sel...

We propose an unsupervised probabilistic model for zero pronoun resolution. To our knowledge, this is the first such model that (1) is trained on zero pronouns in an unsupervised manner; (2) jointly identifies and resolves anaphoric zero pronouns; and (3) exploits discourse information provided by a salience model. Experiments demonstrate that our unsupervised model significantly outperforms it...

Previous approaches to pronominalization have largely been theoretical rather than applied in nature. Frequently, such methods are based on Centering Theory, which deals with the resolution of anaphoric pronouns. But it is not clear that complex theoretical mechanisms, while having satisfying explanatory power, are necessary for the actual generation of pronouns. We first illustrate examples of...

Behavioral studies investigating the influence of the relative word frequency of antecedent nouns on the processing of anaphoric pronouns have yielded contradictory results. While some researchers found no effect of an antecedent's frequency of occurrence on coreference resolution [J. Simner, R. Smyth, Phonological activation in anaphoric lexical access (ALA), Brain Lang. 68 (1999) 40-45], othe...

Handling of human language by computer is a very intricate and complex task. In natural languages, sentences are usually part of discourse units just as words are part of sentences. Anaphora resolution plays a significant role in discourse analysis for chopping larger discourse units into smaller ones. This process is done for the purpose of better understanding and making easier the further pr...

Knowledge of the anaphoricity of a noun phrase might be profitably exploited by a coreference system to bypass the resolution of non-anaphoric noun phrases. Perhaps surprisingly, recent attempts to incorporate automatically acquired anaphoricity information into coreference systems, however, have led to the degradation in resolution performance. This paper examines several key issues in computi...