首页> 外国专利> Iteratively learning coreference embeddings of noun phrases using feature representations that include distributed word representations of the noun phrases

Iteratively learning coreference embeddings of noun phrases using feature representations that include distributed word representations of the noun phrases

机译:使用包括名词短语的分布式单词表示在内的特征表示来迭代学习名词短语的共指嵌入

摘要

Methods and apparatus related to determining coreference resolution using distributed word representations. Distributed word representations, indicative of syntactic and semantic features, may be identified for one or more noun phrases. For each of the one or more noun phrases, a referring feature representation and an antecedent feature representation may be determined, where the referring feature representation includes the distributed word representation, and the antecedent feature representation includes the distributed word representation augmented by one or more antecedent features. In some implementations the referring feature representation may be augmented by one or more referring features. Coreference embeddings of the referring and antecedent feature representations of the one or more noun phrases may be learned. Distance measures between two noun phrases may be determined based on the coreference embeddings.
机译:与使用分布式词表示来确定共指解析度有关的方法和装置。可以为一个或多个名词短语识别表示语法和语义特征的分布式单词表示。对于一个或多个名词短语中的每一个,可以确定指称特征表示和先行特征表示,其中指称特征表示包括分布式单词表示,并且先行特征表示包括由一个或多个先决条件扩展的分布式单词表示。特征。在一些实施方式中,可以通过一个或多个参考特征来增强参考特征表示。可以学习一个或多个名词短语的指称和先行特征表示的共指嵌入。两个名词短语之间的距离量度可以基于共同引用嵌入来确定。

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