Abstract
We have presented a simple algorithm to noun phrases interpretation based on hand-crafted knowledge-base containing detailed semantic information. The main idea is to define a set of relations that can hold between the words and use a semantic lexicon including semantic classifications and collocation features to automatically assign relations to noun phrases. We divide the NPs into two kinds of types: NPs with one verb or non-consecutive verbs and NPs with consecutive verbs, and design two different labeling methods according to their syntactic and semantic features. For the first kind of NPs we report high precision, recall and F-score on a dataset with nine semantic relations, and for the second type the results are also promising on a dataset with four relations. We create a valuable manually-annotated resource for noun phrases interpretation, which we make publicly available with the hope to inspire further research in noun phrases interpretation.
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References
Lapata, M.: The automatic interpretation of nominalizations. In: 17th National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence, pp. 716–721. AAAI Press (2000)
Rosario, B., Hearst, M., Fillmore, C.: The descent of hierarchy, and selection in relational semantics. In: Meeting on Association for Computational Linguistics, pp. 247–254. Association for Computational Linguistics, Philadelphia (2002)
Girju, N., et al.: SemEval-2007 Task 04: classification of semantic relations between nominals. In: 4th Proceeding of International Workshop on Semantic Evaluations (SemEval-2007), pp. 13–18. Association for Computational Linguistics, Prague (2007)
Rosario, B., Hearst, M., Fillmore, C.: Classifying the semantic relations in noun compounds via a domain-specific lexical hierarchy. In: Lee, L., Harman, D. (eds.) Proceedings of EMNLP (Empirical Methods in Natural Language Processing), pp. 247–254 (2001)
Girju, R., Giuglea, A.M., Olteanu, M., et al.: Support vector machines applied to the classification of semantic relations in nominalized noun phrases. In: Proceedings of the HLT-NAACL Workshop on Computational Lexical Semantics, pp. 68—75. Association for Computational Linguistics (2004)
Nastase, V., Sayyad-Shirabad, J., Sokolova, M., et al.: Learning noun-modifier semantic relations with corpus-based and WordNet-based features. In: National Conference on Artificial Intelligence, pp. 781–786. AAAI Press (2006)
Tratz, S., Hovy, E., et al.: A Taxonomy, dataset, and classifier for automatic noun compound interpretation. In: 48th Proceeding of the Annual Meeting of the Association for Computational Linguistics, pp. 678–687 (2010)
Dima, C., Hinrichs, E.: Automatic noun compound interpretation using deep neutral networks and embeddings. In: 11th Proceeding of the International Conference on Computational Semantics, pp. 173–183 (2015)
Lijie, W.: Research on Chinese semantic dependency analysis. Doctoral dissertation. Harbin Institute of Technology (2010)
Yu, D.: Dependency graph based Chinese semantic parsing. Doctoral dissertation. Harbin Institute of Technology (2014)
Weidong, Z.: Principles of determining semantic categories and the relativity of semantic categories. World Chin. Teach. 2, 3–13 (2001)
Hui, W.: Structure and application of the semantic knowledge-base of modern Chinese. Appl. Linguist. 2(1), 134–141 (2006)
Hui, W., Weidong, Z.: New progress of the semantic knowledge-base of contemporary Chinese. In: 7th Joint Academic Conference on Computational Linguistics, Harbin (2003)
Li, Y., Shao, Y.: Annotating Chinese noun phrases based on semantic dependency graph. In: 21st International Conference on Asian Language Processing, pp. 18–21. IEEE, Tainan (2016)
Acknowledgments
Thanks to National Natural Science Foundation of China (NSFC) via Grant 61170144, Major Program of China’s National Linguistics Work Committee during the twelfth five-year plan (ZDI125-41), Young and Middle Aged Academic Cadre Support Plan of Beijing Language and Culture University (501321303), Graduate Innovation Foundation in 2017 (17YCX137).
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Li, Y., Shao, Y., Yang, H. (2017). Semantic Dependency Labeling of Chinese Noun Phrases Based on Semantic Lexicon. In: Sun, M., Wang, X., Chang, B., Xiong, D. (eds) Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data. NLP-NABD CCL 2017 2017. Lecture Notes in Computer Science(), vol 10565. Springer, Cham. https://doi.org/10.1007/978-3-319-69005-6_20
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