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Predicate-Argument Analysis to Build a Phraseology Module and to Increase Conceptual Relation Expressiveness

机译:谓词参数分析构建了一个概念性模块并增加了概念关系表达力

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EcoLexicon, a multilingual and multimodal terminological knowledge base (TKB) on the environment, needs improvements: more expressive non-hierarchical relations and a phraseology module consistent with knowledge representation in the other modules of the TKB. Both issues must be addressed by analyzing predicate-argument structure in text. In this paper, we explain our methodology for predicate-argument analysis with the case study on the conceptual relation affects. We take a semi-automatic approach to extract term-verb-term collocates with Sketch Engine [1]. Then the verbs are classified according to the lexical domains proposed by Faber & Mairal [2] and the arguments in conceptual categories based on the knowledge contained in EcoLexicon. To validate the lexical domains and conceptual categories, an automatic clustering method based on word2vec [3] is applied. The analysis of verbs and arguments contributes to the refinement of our semantic relations and categories as well as to the population of the phraseological module.
机译:Ecolexicon,对环境的多语言和多模式术语知识库(TKB),需要改进:更具表现力的非等级关系和一项与TKB的其他模块中的知识表示符合的言论模块。必须通过分析文本中的谓词参数结构来解决这两个问题。在本文中,我们解释了我们对概念关系影响的案例研究的谓词论证分析方法。我们采取半自动方法提取与草图引擎[1]的术语动词术语。然后,动词根据Faber&Mairal [2]提出的词汇域和基于Ecolexicon中包含的知识的概念类别中的词汇域分类。要验证词汇域和概念类别,应用了基于Word2VEC [3]的自动聚类方法。动词和论据的分析有助于改进我们的语义关系和类别以及酶学模块的人口。

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