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All Fragments Count in Parser Evaluation

机译:解析器评估中的所有片段计数

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摘要

PARSEVAL, the default paradigm for evaluating constituency parsers, calculates parsing success (Precision/Recall) as a function of the number of matching labeled brackets across the test set. Nodes in constituency trees, however, are connected together to reflect important linguistic relations such as predicate-argument and direct-dominance relations between categories. In this paper, we present FREVAL, a generalization of PARSEVAL, where the precision and recall are calculated not only for individual brackets, but also for co-occurring, connected brackets (i.e. fragments). FREVAL fragments precision (FLP) and recall (FLR) interpolate the match across the whole spectrum of fragment sizes ranging from those consisting of individual nodes (labeled brackets) to those consisting of full parse trees. We provide evidence that FREVAL is informative for inspecting relative parser performance by comparing a range of existing parsers.
机译:PARSEVAL是评估选区解析器的默认范例,它根据整个测试集中匹配的带括号的括号的数量来计算解析成功(精确度/调用率)。但是,选区树中的节点连接在一起以反映重要的语言关系,例如类别之间的谓词参数和直接支配关系。在本文中,我们介绍了FREVAL,这是PARSEVAL的概括,其中不仅针对单个括号计算了精度和召回率,而且还针对同时出现的相连括号(即片段)计算了精度和召回率。 FREVAL片段精度(FLP)和查全率(FLR)在整个片段大小范围内进行匹配插值,范围从单个节点组成的片段(标记为括号)到完整解析树组成的片段。通过比较一系列现有解析器,我们提供了FREVAL有助于检查相对解析器性能的证据。

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