Anaphora Resolution In Multi-Person Dialogues

2004

This paper describes an extension of the dar-algorithm (Navarretta, 2004) for resolving intersentential pronominal anaphors referring to individual and abstract entities in texts and dialogues. In dar individual entities are resolved combining models which identify high degree of salience with high degree of givenness (topicality) of entities in the hearer's cognitive model, e.g. (Grosz et al., 1995), with Hajičová et al.'s (1990) salience account which assigns the highest degree of salience to entities in the focal part of an utterance in Information Structure terms, which often introduce new information in discourse. Anaphors referring to abstract entities are resolved with an extension of the algorithm presented by Eckert and Strube (2000). The extended dar-algorithm accounts for differences in the resolution mechanisms of different types of Danish pronouns. Manual tests of the algorithm show that dar performs better than other resolution algorithms on the same data.

Information Science and Technology, 2001

The linguistic phenomenon of anaphora has been monopolising the attention of linguists and computational linguists for some time now, leading to various interpretations. Basically, anaphora is the phenomenon of reiteration of an entity (called “antecedent”) by a reference (called “ ...

Journal of Computer Science, 2007

Anaphora resolution attempts to determine the correct antecedent of an anaphor (the term pointing back). In what follows, we propose an algorithm for the resolution of anaphoric pronouns that relies on lexical and syntactic knowledge incorporated in a modular approach based on constraints and preferences. Our objective was to find the correct antecedent to the following subject pronouns (il, ils, elle, elles), object pronouns (l', le, la, les) and possessive pronouns (son, sa, ses, leur, leurs) in unrestricted texts. We also identify and eliminate pleonastic pronouns and discard candidates appearing in appositions. Moreover we use a focus mechanism to determine salient entities. The algorithm, implemented in Prolog, realizes a success rate of 68%, which was considered a good performance for unrestricted French texts.

2015

The linguistic phenomenon of anaphora has been monopolising the attention of linguists and computational linguists for some time now, leading to various interpretations. Basically, anaphora is the phenomenon of reiteration of an entity (called “antecedent”) by

1995

ArXiv, 2019

Anaphora resolution is a challenging task which has been the interest of NLP researchers for a long time. Traditional resolution techniques like eliminative constraints and weighted preferences were successful in many languages. However, they are ineffective in free word order languages like most SouthAsian languages.Heuristic and rule-based techniques were typical in these languages, which are constrained to context and this http URL this paper, we venture a new strategy us-ing neural networks for resolving anaphora in human-human dialogues. The architecture chiefly consists of three components, a shallow parser for extracting features, a feature vector generator which produces the word embed-dings, and a neural network model which will predict the antecedent mention of an anaphora.The system has been trained and tested on Telugu conversation corpus we generated. Given the advantage of the semantic information in word embeddings and appending actor, gender, number, person and part ...

2007

Anaphora resolution in human-machine dialogue systems is often based on models and algorithms that were designed for text. But dialogue brings out a situation, i.e., an immediate physical environment and events that are perceived simultaneously by the participants. This situation can be at the origin of referential expressions called "exophora", "antecedentless anaphora" or "anaphora with a non-linguistic antecedent". Attributing some referents to such expressions is difficult for two reasons. First, because situational factors are numerous and implicit. Second, because ambiguities can appear between a potential situational antecedent and a potential linguistic one. In this paper we focus on the nature of situational factors and we investigate how they can be taken into account when doing anaphora resolution in dialogue and then in text. Our points of departure are the notion of salience and the nature of the events that intervene in dialogue and that c...

Springer eBooks, 1981

A problem that all computer-based natural language understanding (NLU) systems encounter is that of linguistic reference, and in partic ular anaphora (abbreviated reference). For example, in a text as simple as: Nadia showed sue her new car. orange. The seats were Day-Glo knowing that "her" probably means Nadia and not Sue and that "the seats" means the seats of Nadia's new car is not a simple task. 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. The problem is first examined in detail, and examples are given of many different types of anaphor, some of which have been ignored by previous authors. The approaches taken in traditional systems are then described and abstracted and it is shown why they were inadequate, and why discourse theme and anaphor ic focus need to be taken into account. The strengths and weaknesses of current anaphora theories and approaches are evaluated . The thesis closes with a list of some remaining research problems.

Proceedings of the 1st SIGdial workshop on Discourse and dialogue -, 2000

In this paper 1 I describe the use of Danish pronouns and deictics in dialogues. Then I present an adaptation to Danish of Eckert and Strube's algorithm for resolving anaphora referring to individual NPs and abstract objects in English dialogues . The adapted algorithm is tested on four Danish dialogues from two dialogue collections and the results obtained are evaluated.

Computational Linguistics, 1994

This paper presents an algorithm for identifying the noun phrase antecedents of third person pronouns and lexical anaphors (reflexives and reciprocals). The algorithm applies to the syntactic representations generated by McCord's Slot Grammar parser and relies on salience ...