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ARTIFICIAL INTELLIGENCE BASED CORPUS ENRICHMENT FOR KNOWLEDGE POPULATION AND QUERY RESPONSE

机译:基于人工智能的语料库富集,用于知识人口和查询响应

摘要

In some examples, artificial intelligence based corpus enrichment for knowledge population and query response may include generating, based on annotated training documents, an entity and relation annotation model, identifying, based on application of the entity and relation annotation model to a document set that is to be annotated, entities and relations between the entities for each document of the document set to generate an annotated document set, and categorizing each annotated document into a plurality of categories. Artificial intelligence based corpus enrichment may include determining whether an identified category includes a specified number of annotated documents, and if not, additional annotated documents may be generated for the identified category that may represent a corpus. Further, artificial intelligence based corpus enrichment may include training, using the corpus, an artificial intelligence based decision support model, and utilizing the artificial intelligence based decision support model to respond to an inquiry.
机译:在一些示例中,用于知识人口和查询响应的基于人工智能的语料库充实可以包括基于带注释的训练文档生成实体和关系注释模型,基于将实体和关系注释模型应用于文档集来进行识别。为了进行注释,针对文档集合的每个文档的实体和实体之间的关系以生成带注释的文档集合,并将每个带注释的文档分类为多个类别。基于人工智能的语料库充实可以包括确定所识别的类别是否包括指定数量的带注释的文档,并且如果没有,则可以为所识别的类别生成可以代表语料库的附加带注释的文档。此外,基于人工智能的语料库充实可以包括使用语料库训练基于人工智能的决策支持模型,并利用基于人工智能的决策支持模型来响应查询。

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