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Enhancing Brazilian Portuguese Textual Entailment Recognition with a Hybrid Approach

机译:通过混合方法增强巴西葡萄牙语文本蕴含度的识别

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Previous work on textual entailment has not fully exploited aspects of deep linguistic relations, which have been shown as containing important information for entailment identification. In this study, we present a new method to compute semantic textual similarity between two sentences. Our proposal relies on the integration of a set of deep linguistic relations, lexical aspects and distributed representational resources. We used our method with a large set of annotated data available from the ASSIN Workshop in the PROPOR 2016 event. The achieved results score among the best-known results in the literature. A perceived advantage of our approach is the ability to generate good results even with a small corpus on training tasks.
机译:先前有关文本蕴涵的工作尚未充分利用深层语言关系的方面,这些方面已显示为包含用于蕴涵识别的重要信息。在这项研究中,我们提出了一种计算两个句子之间语义文本相似度的新方法。我们的建议依赖于一组深层语言关系,词汇方面和分布式表示资源的集成。我们将我们的方法与ASSIN Workshop在PROPOR 2016活动中获得的大量带注释的数据结合使用。取得的成绩在文献中名列前茅。我们的方法的一个明显优势是即使在训练任务上语料很少,也能产生良好的结果。

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