9,607 research outputs found

    What is the source of L1 attrition? The effect of recent L1 re-exposure on Spanish speakers under L1 attrition

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    The recent hypothesis that L1 attrition affects the ability to process interface structures but not knowledge representations (Sorace, 2011) is tested by investigating the effects of recent L1 re-exposure on antecedent preferences for Spanish pronominal subjects, using offline judgements and online eye-tracking measures. Participants included a group of native Spanish speakers experiencing L1 attrition (‘attriters’), a second group of attriters exposed exclusively to Spanish before they were tested (‘re-exposed’), and a control group of Spanish monolinguals. The judgement data shows no significant differences between the groups. Moreover, the monolingual and re-exposed groups are not significantly different from each other in the eye-tracking data. The results of this novel manipulation indicate that attrition effects decrease due to L1 re-exposure, and that bilinguals are sensitive to input changes. Taken together, the findings suggest that attrition affects online sensitivity with interface structures rather than causing a permanent change in speakers’ L1 knowledge representations

    Design and enhanced evaluation of a robust anaphor resolution algorithm

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    Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. This paper describes the ROSANA approach, which generalizes the verification of coindexing restrictions in order to make it applicable to the deficient syntactic descriptions that are provided by a robust state-of-the-art parser. By a formal evaluation on two corpora that differ with respect to text genre and domain, it is shown that ROSANA achieves high-quality robust coreference resolution. Moreover, by an in-depth analysis, it is proven that the robust implementation of syntactic disjoint reference is nearly optimal. The study reveals that, compared with approaches that rely on shallow preprocessing, the largely nonheuristic disjoint reference algorithmization opens up the possibility/or a slight improvement. Furthermore, it is shown that more significant gains are to be expected elsewhere, particularly from a text-genre-specific choice of preference strategies. The performance study of the ROSANA system crucially rests on an enhanced evaluation methodology for coreference resolution systems, the development of which constitutes the second major contribution o/the paper. As a supplement to the model-theoretic scoring scheme that was developed for the Message Understanding Conference (MUC) evaluations, additional evaluation measures are defined that, on one hand, support the developer of anaphor resolution systems, and, on the other hand, shed light on application aspects of pronoun interpretation

    Three Algorithms for Competence-Oriented Anaphor Resolution

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    In the last decade, much effort went into the design of robust third-person pronominal anaphor resolution algorithms. Typical approaches are reported to achieve an accuracy of 60-85%. Recent research addresses the question of how to deal with the remaining difficult-toresolve anaphors. Lappin (2004) proposes a sequenced model of anaphor resolution according to which a cascade of processing modules employing knowledge and inferencing techniques of increasing complexity should be applied. The individual modules should only deal with and, hence, recognize the subset of anaphors for which they are competent. It will be shown that the problem of focusing on the competence cases is equivalent to the problem of giving precision precedence over recall. Three systems for high precision robust knowledge-poor anaphor resolution will be designed and compared: a ruleset-based approach, a salience threshold approach, and a machine-learning-based approach. According to corpus-based evaluation, there is no unique best approach. Which approach scores highest depends upon type of pronominal anaphor as well as upon text genre

    Coreference-Based Summarization and Question Answering: a Case for High Precision Anaphor Resolution

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    Approaches to Text Summarization and Question Answering are known to benefit from the availability of coreference information. Based on an analysis of its contributions, a more detailed look at coreference processing for these applications will be proposed: it should be considered as a task of anaphor resolution rather than coreference resolution. It will be further argued that high precision approaches to anaphor resolution optimally match the specific requirements. Three such approaches will be described and empirically evaluated, and the implications for Text Summarization and Question Answering will be discussed

    Resolving anaphoric references on deficient syntactic descriptions

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    Syntactic coindexing restrictions are by now known to be of central importance to practical anaphor resolution approaches. Since, in particular due to structural ambiguity, the assumption of the availability of a unique syntactic reading proves to be unrealistic, robust anaphor resolution relies on techniques to overcome this deficiency. In this paper, two approaches are presented which generalize the verification of coindexing constraints to de cient descriptions. At first, a partly heuristic method is described, which has been implemented. Secondly, a provable complete method is specified. It provides the means to exploit the results of anaphor resolution for a further structural disambiguation. By rendering possible a parallel processing model, this method exhibits, in a general sense, a higher degree of robustness. As a practically optimal solution, a combination of the two approaches is suggested

    Reference resolution in multi-modal interaction: Preliminary observations

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    In this paper we present our research on multimodal interaction in and with virtual environments. The aim of this presentation is to emphasize the necessity to spend more research on reference resolution in multimodal contexts. In multi-modal interaction the human conversational partner can apply more than one modality in conveying his or her message to the environment in which a computer detects and interprets signals from different modalities. We show some naturally arising problems but do not give general solutions. Rather we decide to perform more detailed research on reference resolution in uni-modal contexts to obtain methods generalizable to multi-modal contexts. Since we try to build applications for a Dutch audience and since hardly any research has been done on reference resolution for Dutch, we give results on the resolution of anaphoric and deictic references in Dutch texts. We hope to be able to extend these results to our multimodal contexts later
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