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Verification, Reproduction and Replication of NLP Experiments: a Case Study on Parsing Universal Dependencies

机译:NLP实验的验证,再现和复制:解析普遍依赖性的案例研究

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As in any field of inquiry that depends on experiments, the verifiability of experimental studies is important in computational linguistics. Despite increased attention to verification of empirical results, the practices in the field are unclear. Furthermore, we argue, certain traditions and practices that are seemingly useful for verification may in fact be counterproductive. We demonstrate this through a set of multi-lingual experiments on parsing Universal Dependencies treebanks. In particular, we show that emphasis on exact replication leads to practices (some of which are now well established) that hide the variation in experimental results, effectively hindering verifiability with a false sense of certainty. The purpose of the present paper is to highlight the magnitude of the issues resulting from these common practices with the hope of instigating further discussion. Once we, as a community, are convinced about the importance of the problems, the solutions are rather obvious, although not necessarily easy to implement.
机译:与取决于实验的任何调查领域,实验研究的可验证性在计算语言学中很重要。尽管对经验结果的核查增加了关注,但该领域的实践尚不清楚。此外,我们争辩,似乎对验证似乎有用的某些传统和实践可能是对策。我们通过一组关于解析通用依赖性树木银行的多语言实验来展示这一点。特别是,我们表明强调精确的复制导致实践(现在的一些人建立得很好)隐藏了实验结果的变化,有效地阻碍了验证性的可验证性。本文的目的是突出这些常见做法因煽动进一步讨论而导致的问题的大小。一旦我们作为一个社区,都信服了问题的重要性,解决方案相当明显,尽管不一定易于实施。

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