Automatic validation of compositionality vs non-compositionality is a very challenging problem in NLP. A very small number of papers in literature report results in this particular problem. Recently, some new approaches have arised with respect to this particular linguistic task. One of these approaches that have called our attention is based on what authors call “lexical domain”. In this paper, we analyze the use of Pointwise Mutual Information for constructing thesauri on the fly, which can be further employed instead of dictionaries for determining whether or not a given phraseological unit is compositional or not. The experimental results carried out in this paper show that this dissimilarity measure (PMI), can effectively be used when determining compositionality of a given verbal phraseological unit. Moreover, we show that the use of thesauri improves the results obtained in comparison with those experiments employing dictionaries, highlighting the use of self-constructed lexical resources which are, in fact, taking advantage of the same vocabulary of the target dataset.

中文翻译：

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在语言短语单位验证任务中使用自动构建的叙词表而不是词典

在NLP中，自动验证合成与非合成是一个非常具有挑战性的问题。文献报告中的论文数量很少，导致了这个特殊问题。近来，关于这种特殊的语言任务出现了一些新的方法。这些引起我们关注的方法之一是基于作者所谓的“词法领域”。在本文中，我们分析了使用点向互信息来动态构建叙词表的方法，可以进一步使用它代替字典来确定给定的短语单元是否组成。本文进行的实验结果表明，这种相异性度量（PMI）在确定给定语言短语单元的组成时可以有效地使用。此外，