Abstract
Most previous entity extraction studies focus on a small set of coarse-grained classes, such as person etc. However, the distribution of entities within query logs of search engine indicates that users are more interested in a wider range of fine-grained entities, such as GRAMMY winner and Ivy League member etc. In this paper, we present a semi-supervised method to extract fine-grained entities from an open-domain corpus. We build a graph based on entities in coordinate lists, which are html nodes with the same tag path of the DOM trees. Then class labels are propagated over the graph from known entities to unknowns. Experiments on a large corpus from ClueWeb09a dataset show that our proposed approach achieves the promising results.
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References
Guo, J., et al.: Named entity recognition in query. In: Proceedings of the 32nd International ACM SIGIR Conference on Research and Development in Information Retrieval, Boston, MA, USA, pp. 267–274. ACM (2009)
Jiang, P., et al.: Wiki3C: exploiting wikipedia for context-aware concept categorization. In: Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, Rome, Italy, pp. 345–354. ACM (2013)
Wang, F., Zhang, C.: Label propagation through linear neighborhoods. In: Proceedings of the 23rd International Conference on Machine Learning, Pittsburgh, Pennsylvania, pp. 985–992. ACM (2006)
Ekbal, A., et al.: Assessing the challenge of fine-grained named entity recognition and classification. In: Proceedings of the 2010 Named Entities Workshop, Uppsala, Sweden, pp. 93–101. Association for Computational Linguistics (2010)
Ling, X., Weld, D.S.: Fine-Grained Entity Recognition. In: Proceedings of the 26th Conference on Artificial Intelligence, AAAI (2012)
Limaye, G., Sarawagi, S., Chakrabarti, S.: Annotating and searching web tables using entities, types and relationships. Proc. VLDB Endow. 3(1-2), 1338–1347 (2010)
Weischedel, R., Brunstein, A.: Bbn pronoun coreference and entity type corpus. Linguistic Data Consortium, Philadelphia (2005)
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Yang, Q., Jiang, P., Zhang, C., Niu, Z. (2013). Extracting Fine-Grained Entities Based on Coordinate Graph. In: Métais, E., Meziane, F., Saraee, M., Sugumaran, V., Vadera, S. (eds) Natural Language Processing and Information Systems. NLDB 2013. Lecture Notes in Computer Science, vol 7934. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38824-8_40
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DOI: https://doi.org/10.1007/978-3-642-38824-8_40
Publisher Name: Springer, Berlin, Heidelberg
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