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Exploiting naive vs expert discourse annotations: an experiment using lexical cohesion to predict Elaboration / Entity-Elaboration confusions

机译:利用天真与专家话语注释:使用词汇衔接来预测细化/实体-细化混淆的实验

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This paper brings a contribution to the field of discourse annotation of corpora. Using ANN-ODIS, a french corpus annotated with discourse relations by naive and expert annota-tors, we focus on two of them, Elaboration and Entity-Elaboration. These two very frequent relations are (a) often confused by naive annotators (b) difficult to detect automatically as their signalling is poorly studied. We propose to use lexical cohesion to differentiate between them, and show that Elaboration is more cohesive than Entity-Elaboration. We then integrate lexical cohesion cues in a classification experiment, obtaining highly satisfying results.
机译:本文为语料库的话语注释领域做出了贡献。使用ANN-ODIS,这是一种由天真的和专家注释者注释的具有话语关系的法语语料库,我们将重点放在其中的两个方面:精化和实体精化。这两个非常频繁的关系(a)经常被幼稚的注释者所混淆(b)由于对其信号的研究很少,因此很难自动检测到。我们建议使用词法内聚来区分它们,并表明细化比实体细化具有更大的内聚性。然后,我们将词汇衔接线索整合到分类实验中,获得了令人满意的结果。

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