Research on Coreference Resolution Based on Conditional Random Fields
نویسندگان
چکیده
منابع مشابه
Chinese Chunking based on Conditional Random Fields
In this paper, we proposed an approach for Chinese chunking based on the Conditional Random Fields model (CRFs). For sequence labeling, CRFs has advantages over generative models. Furthermore, Chinese chunking is a difficult sequence labeling task. This paper describes how to use CRFs for Chinese chunking via capturing the arbitrary and overlapping features. We defined different types of featur...
متن کاملSkipCor: Skip-Mention Coreference Resolution Using Linear-Chain Conditional Random Fields
Coreference resolution tries to identify all expressions (called mentions) in observed text that refer to the same entity. Beside entity extraction and relation extraction, it represents one of the three complementary tasks in Information Extraction. In this paper we describe a novel coreference resolution system SkipCor that reformulates the problem as a sequence labeling task. None of the exi...
متن کاملStructured Local Training and Biased Potential Functions for Conditional Random Fields with Application to Coreference Resolution
Conditional Random Fields (CRFs) have shown great success for problems involving structured output variables. However, for many real-world NLP applications, exact maximum-likelihood training is intractable because computing the global normalization factor even approximately can be extremely hard. In addition, optimizing likelihood often does not correlate with maximizing task-specific evaluatio...
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"Coreference resolution" or "finding all expressions that refer to the same entity" in a text, is one of the important requirements in natural language processing. Two words are coreference when both refer to a single entity in the text or the real world. So the main task of coreference resolution systems is to identify terms that refer to a unique entity. A coreference resolution tool could be...
متن کاملConditional Random Fields based Pronominal Resolution in Tamil
This paper deals with Tamil pronominal resolution using Conditional Random Fields a machine learning approach. A detailed linguistic analysis of Tamil pronominals and its antecedence occurring in various syntactic constructs is done, which led to the selection of appropriate features for CRF approach. The syntactic features thus identified made the system learn most frequently occurring pronoun...
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ژورنال
عنوان ژورنال: DEStech Transactions on Environment, Energy and Earth Sciences
سال: 2021
ISSN: 2475-8833
DOI: 10.12783/dteees/peees2020/35461