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Due to the special characteristics and challenges in Chinese language, event extraction in Chinese is much more difficult than that in English. In particular, the state-of-the-art Chinese event extraction systems suffer much from the low recall in trigger identification due to the failure in identifying unknown triggers and the inconsistency in identifying trigger mentions. To resolve these two issues, this paper proposes an inference mechanism to infer unknown triggers via the compositional semantics inside Chinese words and another inference mechanism to recover trigger mentions via the discourse consistency between Chinese trigger mentions. Here, various morphological structures are explored to better represent the compositional semantics inside Chinese triggers and automatically identify the head morpheme as the governing sememe of a trigger in inferring unknown triggers. Evaluation on the ACE 2005 Chinese corpus justifies the effectiveness of our approach over a strong baseline in Chinese event extraction, in particular trigger identification. 相似文献
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We propose answer extraction and ranking strategies for definitional question answering using linguistic features and definition terminology. A passage expansion technique based on simple anaphora resolution is introduced to retrieve more informative sentences, and a phrase extraction method based on syntactic information of the sentences is proposed to generate a more concise answer. In order to rank the phrases, we use several evidences including external definitions and definition terminology. Although external definitions are useful, it is obvious that they cannot cover all the possible targets. The definition terminology score which reflects how the phrase is definition-like is devised to assist the incomplete external definitions. Experimental results show that the proposed answer extraction and ranking method are effective and also show that our proposed system is comparable to state-of-the-art systems. 相似文献