A Machine Learning Approach to Pronoun Resolution in Spoken Dialogue
نویسندگان
چکیده
We apply a decision tree based approach to pronoun resolution in spoken dialogue. Our system deals with pronouns with NPand non-NP-antecedents. We present a set of features designed for pronoun resolution in spoken dialogue and determine the most promising features. We evaluate the system on twenty Switchboard dialogues and show that it compares well to Byron’s (2002) manually tuned system.
منابع مشابه
Second - person pronoun resolution in multi - party spoken English dialogue ∗
This paper discusses the problem of second-person pronoun resolution in dialogue: determining who (if anyone) the word ‘you’ refers to. We motivate the task, and break it down into three distinct subtasks – distinguishing generic from deictic uses, distinguishing singular from plural uses, and determining individual reference. We then describe a dataset and series of supervised classification e...
متن کاملAntelogue: Pronoun Resolution for Text and Dialogue
Antelogue is a pronoun resolution prototype designed to be released as off-the-shelf software to be used autonomously or integrated with larger anaphora resolution or other NLP systems. It has modules to handle pronouns in both text and dialogue. In Antelogue, the problem of pronoun resolution is addressed as a two-step process: a) acquiring information about properties of words and the entitie...
متن کاملA Machine Learning Approach to Anaphora Resolution in Dialogue based Intelligent Tutoring Systems
Anaphora resolution is a central topic in dialogue and discourse that deals with finding the referent of a pronoun. It plays a critical role in conversational Intelligent Tutoring Systems (ITSs) as it can increase the accuracy of assessing students’ mental model based on their natural language inputs. Although the task of anaphora resolution is one of the most studied problems in Natural Langua...
متن کاملUsing 'Low-cost' Learning Features for Pronoun Resolution
We investigate a machine learning approach to Portuguese pronoun resolution. We presently focus on so-called ‘low-cost’ learning features readily obtainable from the output of a part-of-speech tagger, and we largely bypass deep syntactic and semantic analysis. Preliminary results show significant improvement in resolution precision and recall, and are comparable to existing rule-based approache...
متن کاملUsing ‘Low-cost’ Learning Features for Pronoun Resolution
We investigate a machine learning approach to Portuguese pronoun resolution. We presently focus on so-called ‘low-cost’ learning features readily obtainable from the output of a part-of-speech tagger, and we largely bypass deep syntactic and semantic analysis. Preliminary results show significant improvement in resolution precision and recall, and are comparable to existing rule-based approache...
متن کامل