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Truth Is a Lie: Crowd Truth and the Seven Myths of Human Annotation

机译:真理是谎言:人群真理和人类注释的七个神话

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摘要

Big data is having a disruptive impact across the sciences. Human annotation of semantic interpretation tasks is a critical part of big data semantics, but it is based on an antiquated ideal of a single correct truth that needs to be similarly disrupted. We expose seven myths about human annotation, most of which derive from that antiquated ideal of truth, and dispell these myths with examples from our research. We propose a new theory of truth, crowd truth, that is based on the intuition that human interpretation is subjective, and that measuring annotations on the same objects of interpretation (in our examples, sentences) across a crowd will provide a useful representation of their subjectivity and the range of reasonable interpretations.
机译:大数据正在对整个科学产生破坏性影响。人工解释语义解释任务是大数据语义的关键部分,但它基于单个正确真理的过时理想,该理想同样需要被破坏。我们揭露了关于人类注释的七个神话,其中大多数来自于过时的真理真理,并通过我们的研究实例消除了这些神话。我们提出了一种新的真理理论,即人群真理,该理论基于人类解释是主观的直觉,而在人群中测量相同解释对象(在我们的示例中为句子)的注释将为他们提供有用的表示主观性和合理解释的范围。

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