李斌,闻媛,宋丽,卜丽君,曲维光,薛念文. 融合概念对齐信息的中文AMR语料库的构建[J]. 中文信息学报, 2017, 31(6): 93-102.
LI Bin, WEN Yuan, SONG Li, BU Lijun, QU Weiguang, XUE Nianwen. Construction of Chinese Abstract Meaning Representation Corpus with Concept-to-word Alignment. , 2017, 31(6): 93-102.
Construction of Chinese Abstract Meaning Representation Corpus with Concept-to-word Alignment
LI Bin1, WEN Yuan1, SONG Li1, BU Lijun1, QU Weiguang2,3, XUE Nianwen4
1.School of Chinese Language and Literature, Nanjing Normal University, Nanjing, Jiangsu 210023, China; 2.School of Computer Science and Technology, Nanjing Normal University, Nanjing, Jiangsu 210023, China;3.Fujian Provincial Key Laboratory of Information Processing and Intelligent Control, Minjiang University, Fuzhou, Fujian 350121, China;4.Michtom School of Computer Science, Brandeis University, Waltham, MA 02453, USA
Abstract：As a new sentence-level meaning representation, abstract meaning representation (AMR) uses a rooted acyclic directed graph to represent the meaning of a sentence. A large AMR bank has been constructed for English, but the concepts of an AMR graph are not aligned to the words in a sentence, which increases the difficulty in manual annotation as well as automatic parsing. This paper describes the construction of a Chinese AMR corpus, based on guidelines adapted from English for Chinese-specific properties. We also designs an efficient annotation framework that incorporates concept-to-word alignment, taking advantage of the morphology-poor nature of Chinese. We have annotated the AMRs of 6 923 sentences selected from the Chinese TreeBank, among which 48% of the sentences are graphs, 1% of the sentences are cycles, and 32% have non-projective subtrees. We plan to publicly release this data for linguistic and NLP research.
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