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Generalizing Sub-sentential Paraphrase Acquisition across Original Signal Type of Text Pairs

机译:跨文本对的原始信号类型泛化亚句子释义获取

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This paper describes a study on the impact of the original signal (text, speech, visual scene, event) of a text pair on the task of both manual and automatic sub-sentential paraphrase acquisition. A corpus of 2,500 annotated sentences in English and French is described, and performance on this corpus is reported for an efficient system combination exploiting a large set of features for paraphrase recognition. A detailed quantified typology of sub-sentential paraphrases found in our corpus types is given.
机译:本文介绍了文本对原始信号(文本,语音,视觉场景,事件)对手动和自动子信箱释义的任务的影响的研究。描述了2,500名中的英语和法语句子的语料库,并据报道了这种语料库的性能,用于利用用于解释识别的大集件的有效系统组合。给出了在我们的语料库类型中发现的子信释录的详细量化类型。

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