@inproceedings{hanselowski-etal-2018-ukp,
    title = "{UKP}-Athene: Multi-Sentence Textual Entailment for Claim Verification",
    author = "Hanselowski, Andreas  and
      Zhang, Hao  and
      Li, Zile  and
      Sorokin, Daniil  and
      Schiller, Benjamin  and
      Schulz, Claudia  and
      Gurevych, Iryna",
    booktitle = "Proceedings of the First Workshop on Fact Extraction and {VER}ification ({FEVER})",
    month = nov,
    year = "2018",
    address = "Brussels, Belgium",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W18-5516",
    doi = "10.18653/v1/W18-5516",
    pages = "103--108",
    abstract = "The Fact Extraction and VERification (FEVER) shared task was launched to support the development of systems able to verify claims by extracting supporting or refuting facts from raw text. The shared task organizers provide a large-scale dataset for the consecutive steps involved in claim verification, in particular, document retrieval, fact extraction, and claim classification. In this paper, we present our claim verification pipeline approach, which, according to the preliminary results, scored third in the shared task, out of 23 competing systems. For the document retrieval, we implemented a new entity linking approach. In order to be able to rank candidate facts and classify a claim on the basis of several selected facts, we introduce two extensions to the Enhanced LSTM (ESIM).",
}