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Integrating NLP Tools in a Distributed Environment: A Case Study Chaining a Tagger with a Dependency Parser

机译:在分布式环境中集成NLP工具:案例研究,将Tagger与依赖解析器链接在一起

摘要

The present paper tackles the issue of PoS tag conversion within the framework of a distributed web service platform for the automatic creation of language resources. PoS tagging is now considered a "solved problem"; yet, because of the differences in the tagsets, interchange of the various PoS taggers vailable is still hampered. In this paper we describe the implementation of a PoS-tagged-corpus converter, which is needed for chaining together in a workflow the FreeLing PoS tagger for Italian and the DESR dependency parser, given that these two tools have been developed independently. The conversion problems experienced during the implementation, related to the properties of the different tagsets and of tagset conversion in general, are discussed together with the solutions adopted. Finally, the converter is evaluated by assessing the impact of conversion on the performance of the dependency parser by comparing with the outcome of the native pipeline. From this we learn that in most cases parsing errors are due to actual tagging errors, and not to conversion itself. Besides, information on accuracy loss is an important feature in a distributed environment of (NLP) services, where users need to decide which services best suit their needs
机译:本文在用于自动创建语言资源的分布式Web服务平台的框架内解决了PoS标签转换的问题。 PoS标记现在被认为是“已解决的问题”。然而,由于标签集的差异,各种可用的PoS标签器的互换仍然受到阻碍。在本文中,我们描述了PoS标记语料库转换器的实现,这是在工作流中将意大利语的FreeLing PoS标记器和DESR依赖解析器链接在一起所需的,因为这两个工具是独立开发的。讨论了在实现过程中遇到的转换问题,这些转换问题与不同标签集的属性以及通常的标签集转换有关,并讨论了所采用的解决方案。最后,通过与本地管道的结果进行比较来评估转换对依赖分析器性能的影响,从而评估转换器。由此我们了解到,在大多数情况下,解析错误是由于实际的标记错误引起的,而不是由于转换本身引起的。此外,关于准确性损失的信息是(NLP)服务的分布式环境中的重要功能,在该环境中,用户需要确定最适合其需求的服务

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