Team DOMLIN: Exploiting Evidence Enhancement for the FEVER Shared Task

2019-11-01 · WS 2019 11 · Dominik Stammbach, Guenter Neumann

This paper contains our system description for the second Fact Extraction and VERification (FEVER) challenge. We propose a two-staged sentence selection strategy to account for examples in the dataset where evidence is not only conditioned on the claim, but also on previously retrieved evidence. We use a publicly available document retrieval module and have fine-tuned BERT checkpoints for sentence se- lection and as the entailment classifier. We report a FEVER score of 68.46{\%} on the blind testset.

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RetrievalSentence

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Team Papelo at FEVEROUS: Multi-hop Evidence Pursuit

2021-11-01 · EMNLP (FEVER) 2021 11 · Christopher Malon

We develop a system for the FEVEROUS fact extraction and verification task that ranks an initial set of potential evidence and then pursues missing evidence in subsequent hops by trying to generate it, with a “next hop p…

DOMLIN at SemEval-2019 Task 8: Automated Fact Checking exploiting Ratings in Community Question Answering Forums

2019-06-01 · SEMEVAL 2019 6 · Dominik Stammbach, Stalin Varanasi, Guenter Neumann

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2018-11-01 · WS 2018 11 · Ankur Padia, Francis Ferraro, Tim Finin

We describe our system used in the 2018 FEVER shared task. The system employed a frame-based information retrieval approach to select Wikipedia sentences providing evidence and used a two-layer multilayer perceptron to c…

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The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) Shared Task

2021-11-01 · EMNLP (FEVER) 2021 11 · Rami Aly, Zhijiang Guo, Michael Sejr Schlichtkrull, James Thorne 외

The Fact Extraction and VERification Over Unstructured and Structured information (FEVEROUS) shared task, asks participating systems to determine whether human-authored claims are Supported or Refuted based on evidence r…

Retrieval

Robust Document Retrieval and Individual Evidence Modeling for Fact Extraction and Verification.

2018-11-01 · WS 2018 11 · Tuhin Chakrabarty, Tariq Alhindi, Smar Muresan, a

This paper presents the ColumbiaNLP submission for the FEVER Workshop Shared Task. Our system is an end-to-end pipeline that extracts factual evidence from Wikipedia and infers a decision about the truthfulness of the cl…

Natural Language Inference Retrieval Sentence