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    Iteratively learning coreference embeddings of noun phrases using feature representations that include distributed word representations of the noun phrases
    1.
    发明授权
    Iteratively learning coreference embeddings of noun phrases using feature representations that include distributed word representations of the noun phrases 有权
    使用包括名词短语的分布式单词表示的特征表示迭代地学习名词短语的嵌入式

    公开(公告)号：US09514098B1

    公开(公告)日：2016-12-06

    申请号：US14141182

    申请日：2013-12-26

    Applicant: Google Inc.

    Inventor： Amarnag Subramanya ,  Jingyi Liu ,  Fernando Carlos das Neves Pereira ,  Kai Chen ,  Jay Ponte ,  Rami Al-Rfou′

    IPC: G06F17/21

    CPC classification number: G06F17/21 ,  G06F17/277 ,  G06F17/278

    Abstract: 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.

    Abstract translation: 与使用分布式字表示法确定协同解析相关的方法和设备。 可以为一个或多个名词短语识别表示句法和语义特征的分布式词表示。 对于一个或多个名词短语中的每个，可以确定引用特征表示和先行特征表示，其中引用特征表示包括分布式词表示，并且先行特征表示包括由一个或多个前缀增强的分布式词表示 特征。 在一些实现中，引用特征表示可以由一个或多个引用特征来增强。 可以学习一个或多个名词短语的引用和先行特征表示的核心嵌入。 两个名词短语之间的距离度量可以基于核心嵌入来确定。

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