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Discriminative Strategies to Integrate Multiword Expression Recognition and Parsing

机译:差异策略,以集成多字expression识别和解析

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The integration of multiword expressions in a parsing procedure has been shown to improve accuracy in an artificial context where such expressions have been perfectly pre-identified. This paper evaluates two empirical strategies to integrate multiword units in a real constituency parsing context and shows that the results are not as promising as has sometimes been suggested. Firstly, we show that pre-grouping multiword expressions before parsing with a state-of-the-art recognizer improves multiword recognition accuracy and unlabeled attachment score. However, it has no statistically significant impact in terms of F-score as incorrect multiword expression recognition has important side effects on parsing. Secondly, integrating multiword expressions in the parser grammar followed by a reranker specific to such expressions slightly improves all evaluation metrics.
机译:已经示出了在解析过程中的多个表达式的集成,以提高人工背景中的准确性,其中这些表达式已经完全预先识别。本文评估了两个实证策略,以在真正的选区解析上下文中集成多个单词单元,并表明结果与有时建议的结果不那么承诺。首先,我们表明,在与最先进的识别器中解析之前,预先分组多字级表达式提高了多字识别准确性和未标记的附件分数。然而,由于F-S分数,它没有统计上显着的影响,因为乘以乘以对解析具有重要的副作用。其次,在解析器语法中集成了多字级表达式,然后是特定于此类表达式的重新划分的重新划分的reranker略微改善了所有评估度量。

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