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System and methods for performing NLP related tasks using contextualized word representations

机译:使用上下文化字表示执行NLP相关任务的系统和方法

摘要

Systems, apparatuses, and methods for representing words or phrases, and using the representation to perform NLP and NLU tasks, where these tasks include sentiment analysis, question answering, and conference resolution. Embodiments introduce a type of deep contextualized word representation that models both complex characteristics of word use, and how these uses vary across linguistic contexts. The word vectors are learned functions of the internal states of a deep bidirectional language model (biLM), which is pre-trained on a large text corpus. These representations can be added to existing task models and significantly improve the state of the art across challenging NLP problems, including question answering, textual entailment and sentiment analysis.
机译:用于表示单词或短语的系统,装置和方法,以及使用表示执行NLP和NLU任务,其中这些任务包括情感分析,问题应答和会议分辨率。实施例介绍一种模拟词使用的复杂特征的深层语境化词表示,以及这些在语言上下文中的使用方式。单词vectors是深度双向语言模型(BILM)的内部状态的函数,该函数在大型文本语料库上预先培训。这些表示可以添加到现有的任务模型中,并显着提高了挑战NLP问题的艺术状态,包括问题应答,文本意外和情感分析。

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