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Showing 1 to 4 of 4 for “"Entity detection"”.
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Autoentity: automated entity detection from massive text corpora
Entity detection is one of the fundamental tasks in Natural Language Processing and Information Retrieval. Most existing methods rely on human annotated data and hand-crafted linguistic features, which makes it hard to apply the model to an emerging domain. In this paper, we propose a novel …
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Optimizing cybersecurity knowledge graph question answering: a framework for performance and generalization
… to aid investigators, improving ForensiQ's entity detection speed, and testing performance on rephrased questions. Towards this goal, a Django web application was developed to visualize KGQA reasoning, aid KG exploration, and facilitate the creation of custom KGQA datasets. We also replaced …
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The use of syntactic structure in relationship extraction
… and syntactic features of text along with entity detection information to perform sentence-level relationship extraction tasks. The tasks are to build and test classifiers for the following relationships: employer-employee, organization-location, family, and person-location. Methods of …
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Sepia : semantic parsing for named entities
… parser to create a data structure for each named entity. The parser and grammar design are inspired by Combinatory Categorial Grammar. The data structures are designed to capture semantic dependencies using common syntactic forms. Sepia differs from other natural language parsers in that it does …