Apoorve Tomer - Academia.edu (original) (raw)
Address: Bangalore, India
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FIZ Karlsruhe – Leibniz Institute for Information Infrastructure
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Papers by Apoorve Tomer
Proceedings of the 26th International Conference on World Wide Web Companion, 2017
Assignment of fine-grained types to named entities is gaining popularity as one of the major Info... more Assignment of fine-grained types to named entities is gaining popularity as one of the major Information Extraction tasks due to its applications in several areas of Natural Language Processing. Existing systems use huge knowledge bases to improve the accuracy of the fine-grained types. We designed and developed SANE, a system that uses Wikipedia categories to fine grain the type of the named entities recognized in the textual data. The main contribution of this work is building a named entity typing system without the use of knowledge bases. Through our experiments, 1) we establish the usefulness of Wikipedia categories to Named Entity Typing and 2) we show that SANE's performance is on par with the state-of-the-art.
Proceedings of the 26th International Conference on World Wide Web Companion, 2017
Assignment of fine-grained types to named entities is gaining popularity as one of the major Info... more Assignment of fine-grained types to named entities is gaining popularity as one of the major Information Extraction tasks due to its applications in several areas of Natural Language Processing. Existing systems use huge knowledge bases to improve the accuracy of the fine-grained types. We designed and developed SANE, a system that uses Wikipedia categories to fine grain the type of the named entities recognized in the textual data. The main contribution of this work is building a named entity typing system without the use of knowledge bases. Through our experiments, 1) we establish the usefulness of Wikipedia categories to Named Entity Typing and 2) we show that SANE's performance is on par with the state-of-the-art.