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FEVER: a large-scale dataset for Fact Extraction and VERification
Unlike other tasks and despite recent interest, research in textual claim verification has been hindered by the lack of large-scale manually annotated datasets. In this paper we introduce a newExpand
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Stance Detection with Bidirectional Conditional Encoding
Stance detection is the task of classifying the attitude expressed in a text towards a target such as Hillary Clinton to be "positive", negative" or "neutral". Previous work has assumed that eitherExpand
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Overview of BioCreative II gene mention recognition
Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene nameExpand
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Emergent: a novel data-set for stance classification
We present Emergent, a novel data-set derived from a digital journalism project for rumour debunking. The data-set contains 300 rumoured claims and 2,595 associated news articles, collected andExpand
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The Fact Extraction and VERification (FEVER) Shared Task
We present the results of the first Fact Extraction and VERification (FEVER) Shared Task. The task challenged participants to classify whether human-written factoid claims could be Supported orExpand
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UvA-DARE ( Digital Academic Repository ) Overview of BioCreative II gene mention recognition
Nineteen teams presented results for the Gene Mention Task at the BioCreative II Workshop. In this task participants designed systems to identify substrings in sentences corresponding to gene nameExpand
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Noise reduction and targeted exploration in imitation learning for Abstract Meaning Representation parsing
Semantic parsers map natural language statements into meaning representations, and must abstract over syntactic phenomena, resolve anaphora, and identify word senses to eliminate ambiguousExpand
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Semantic Parsing as Machine Translation
Semantic parsing is the problem of deriving a structured meaning representation from a natural language utterance. Here we approach it as a straightforward machine translation task, and demonstrateExpand
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A Strong Lexical Matching Method for the Machine Comprehension Test
Machine comprehension of text is the overarching goal of a great deal of research in natural language processing. The Machine Comprehension Test (Richardson et al., 2013) was recently proposed toExpand
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A stopping criterion for active learning
Active learning (AL) is a framework that attempts to reduce the cost of annotating training material for statistical learning methods. While a lot of papers have been presented on applying AL toExpand
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