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A Hybrid Entity-Mention Pronoun Resolution Model for German Using Markov Logic Networks

机译:基于马尔可夫逻辑网络的德语混合实体-主语代词解析模型

摘要

This paper presents a hybrid pronoun reso- lution system for German. It uses a simple rule-driven entity-mention formalism to in- crementally process discourse entities. An- tecedent selection is performed based on Markov Logic Networks (MLNs). The hy- brid architecture yields a cheap problem formulation in the MLNs w.r.t. inference complexity but pertains their expressive- ness. We compare the system to a rule- driven baseline and an extension which uses a memory-based learner. We find that the MLN hybrid outperforms its competi- tors by large margins.
机译:本文介绍了一种用于德语的混合代词解析系统。它使用简单的规则驱动的实体提及形式主义来逐步处理话语实体。先验选择是基于马尔可夫逻辑网络(MLN)进行的。混合体系结构可以在MLN中生成便宜的问题表述。推理复杂度,但与它们的表达有关。我们将系统与规则驱动的基准和使用基于内存的学习器的扩展进行比较。我们发现MLN混合动力汽车在很大程度上优于竞争对手。

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