An algorithm for pronominal anaphora resolution
Computational Linguistics
Extracting Patterns and Relations from the World Wide Web
WebDB '98 Selected papers from the International Workshop on The World Wide Web and Databases
StatSnowball: a statistical approach to extracting entity relationships
Proceedings of the 18th international conference on World wide web
TextRunner: open information extraction on the web
NAACL-Demonstrations '07 Proceedings of Human Language Technologies: The Annual Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Open information extraction using Wikipedia
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Open information extraction: the second generation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
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This paper proposes an information extraction model that identifies text patterns representing relations between two entities. It is proposed that, given a set of entity pairs representing a specific relation, it is possible to find text patterns representing such relation within sentences from documents containing those entites. After those text patterns are identified, it is possible to attempt the extraction of a complementary entity, considering the first entity of the relation and the related text patterns are provided. The pattern selection relies on regular expressions, frequency and identification of less relevant words. Modern search engines APIs and HTML parsers are used to retrieve and parse web pages in real time, eliminating the need of a pre-established corpus. The retrieval of document counts within a timeframe is also used to aid in the selection of the entities extracted.