Antecedent (grammar)

About: Antecedent (grammar) is a research topic. Over the lifetime, 1392 publications have been published within this topic receiving 41824 citations.

Referential Choice: Predictability and Its Limits.

Abstract: We report a study of referential choice in discourse production, understood as the choice between various types of referential devices, such as pronouns and full noun phrases. Our goal is to predict referential choice, and to explore to what extent such prediction is possible. Our approach to referential choice includes a cognitively informed theoretical component, corpus analysis, machine learning methods and experimentation with human participants. Machine learning algorithms make use of 25 factors, including referent’s properties (such as animacy and protagonism), the distance between a referential expression and its antecedent, the antecedent’s syntactic role, and so on. Having found the predictions of our algorithm to coincide with the original almost 90% of the time, we hypothesized that fully accurate prediction is not possible because, in many situations, more than one referential option is available. This hypothesis was supported by an experimental study, in which participants answered questions about either the original text in the corpus, or about a text modified in accordance with the algorithm’s prediction. Proportions of correct answers to these questions, as well as participants’ rating of the questions’ difficulty, suggested that divergences between the algorithm’s prediction and the original referential device in the corpus occur overwhelmingly in situations where the referential choice is not categorical.

Computational approach to anaphora resolution in Spanish dialogues

Abstract: This paper presents an algorithm for identifying noun-phrase antecedents of pronouns and adjectival anaphors in Spanish dialogues. We believe that anaphora resolution requires numerous sources of information in order to find the correct antecedent of the anaphor. These sources can be of different kinds, e.g., linguistic information, discourse/dialogue structure information, or topic information. For this reason, our algorithm uses various different kinds of information (hybrid information). The algorithm is based on linguistic constraints and preferences and uses an anaphoric accessibility space within which the algorithm finds the noun phrase. We present some experiments related to this algorithm and this space using a corpus of 204 dialogues. The algorithm is implemented in Prolog. According to this study, 95.9% of antecedents were located in the proposed space, a precision of 81.3% was obtained for pronominal anaphora resolution, and 81.5% for adjectival anaphora.

Children's Acquisition of the Locality Condition for Reflexives and Pronouns.

Abstract: Three experiments investigated the development in young children of two concepts: the antecedent possibilities for reflexives (eg, himself or herself) and pronouns (eg, him or her) In the first experiment, 156 English-speaking children aged 2;6 to 6;6 and 21 adults were tested for their understanding of antecedents within reflexive sentences, pronoun sentences, and gender-control pronoun sentences The results for reflexive sentences were as predicted by the Lexical Learning Hypothesis, but the pronoun sentence results were not Following up this earlier experiment with similar subject groups, the second study tested infinitival structures and gender control for reflexives and the third tested whether the youngest children had the linguistic knowledge that reflexives and pronouns need non-local antecedents In general, when relative patterns rather than absolute scores or ages are considered, the results of the later studies replicated the results of tho earlier experiment: when the target task is to make col:eference judgments between the reflexive or pronoun and the two sentence-internal antecedents, children do differentiate reflexive from pronoun sentences in all experiments, regardless of complement type and the different tasks required However, a developmental delay in acquisition of non-locality condition for pronouns suggests a need for additional investigation of the Lexical Learning Hypothesis (MSE) *****************************a***************************************** Reproductions supplied by EDRS are the best that can be made from the original document ***********************************************************************

Method of and apparatus for automated behavior prediction

Abstract: A computer-implemented method of behavior prediction includes selecting behavior examples having corresponding antecedent candidates, identifying source text descriptions describing the behavior examples, automatically extracting predictors as common themes across all statements and all behavior examples with a language-independent theme extraction process, flagging each behavior example to indicate a presence or absence of the corresponding extracted antecedents in each of the source text descriptions and creating a data array consisting of antecedent columns and behavior example rows, submitting the data array to a pattern classifier to extract patterns among the antecedent candidates and outcomes by training and validating the pattern classifier and predicting a new occurrence of a target behavior by entering a current state of the antecedents to the trained pattern classifier.

Towards More Specific Estimation of Membership Functions for Data-Driven Fuzzy Inference Systems

Abstract: Many fuzzy inference systems are built estimating their parameters from data. In particular, Takagi-Sugeno systems have been used a lot in data-driven fuzzy modeling. In this paper, we investigate one step in the data-driven identification of these models, namely the antecedent estimation when fuzzy clustering is used for estimating antecedent memberships and fuzzy rules. We propose removing noise coming from cluster membership values to obtain more specific antecedent sets, which is important for the interpretability of the models. The results obtained and presented in this paper show that this additional step leads to improved performance of the fuzzy model and higher specificity of the antecedent sets.