State-of-the-art Chinese zero pronoun resolution systems are supervised, thus relying on training data containing manually resolved zero pronouns. To eliminate the reliance on annotated data, we present a generative model for unsupervised Chinese zero pronoun resolution. At the core of our model is a novel hypothesis: a probabilistic pronoun resolver trained on overt pronouns in an unsupervised...

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...

A recently-proposed machine learning approach to reference resolution — the twin-candidate approach — has been shown to be more promising than the traditional single-candidate approach. This paper presents a pronoun interpretation system that extends the twin-candidate framework by (1) equipping it with the ability to identify non-referential pronouns, (2) training different models for handling...

We describe the DARE corpus, an annotated data set focusing on pronoun resolution in tutorial dialogue. Although data sets for general purpose anaphora resolution exist, they are not suitable for dialogue based Intelligent Tutoring Systems. To the best of our knowledge, no data set is currently available for pronoun resolution in dialogue based intelligent tutoring systems. The described DARE c...

We present an approach to pronoun resolution based on syntactic paths. Through a simple bootstrapping procedure, we learn the likelihood of coreference between a pronoun and a candidate noun based on the path in the parse tree between the two entities. This path information enables us to handle previously challenging resolution instances, and also robustly addresses traditional syntactic corefe...

________________________________________________________________________________________________________ Automatic recognition of demonstrative pronouns function in Arabic Anaphora resolution is one of the most difficult tasks in NLP. Classifying pronouns before attempting a task of anaphora resolution is important because to handle the cataphoric pronoun, the system should determine the antece...

Arabic is a relatively free-word order language allowing the positioning of the subject either before its owner verb or after it. Whenever the subject precedes its verb, a personal pronoun has to be associated with the verb to play the role of its subject and enable the proper construction of the full verbal sentence. Sometimes such subject pronoun is explicit, appearing as a suffix to the verb...

The meaning of ‘we’ is usually seen as ‘I þ others’. Russian, along with many other languages, has a construction that allows an overt specification of ‘others’, the so-called Plural Pronoun Construction (PPC), which involves a plural pronoun and a comitative phrase. The syntactic behavior of this comitative phrase differs from that of other withphrases such as VP-adjuncts, NP-adjuncts, and com...

This study provides a detailed analysis of evaluation of English pronoun reference questions which are created automatically by machine. Pronoun reference questions are multiple choice questions that ask test takers to choose an antecedent of a target pronoun in a reading passage from four options. The evaluation was performed from two perspectives: the perspective of English teachers and that ...