Zero-subject Resolution by Probabilistic Model
نویسندگان
چکیده
منابع مشابه
A Fully-Lexicalized Probabilistic Model for Japanese Zero Anaphora Resolution
This paper presents a probabilistic model for Japanese zero anaphora resolution. First, this model recognizes discourse entities and links all mentions to them. Zero pronouns are then detected by case structure analysis based on automatically constructed case frames. Their appropriate antecedents are selected from the entities with high salience scores, based on the case frames and several pref...
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In this work, we improve the performance of intra-sentential zero anaphora resolution in Japanese using a novel method of recognizing subject sharing relations. In Japanese, a large portion of intrasentential zero anaphora can be regarded as subject sharing relations between predicates, that is, the subject of some predicate is also the unrealized subject of other predicates. We develop an accu...
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This paper proposes a method to resolve Japanese zero pronouns by identifying their antecedents. Our method uses a probabilistic model, which is decomposed into syntactic and semantic properties. A syntactic model is trained based on corpora annotated with anaphoric relations. However, a semantic model is trained based on a large-scale unannotated corpus, so as to counter the data sparseness pr...
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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...
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ژورنال
عنوان ژورنال: Journal of Natural Language Processing
سال: 1996
ISSN: 1340-7619,2185-8314
DOI: 10.5715/jnlp.3.4_67