@inproceedings{agirre-etal-2018-risk,
    title = "The risk of sub-optimal use of Open Source {NLP} Software: {UKB} is inadvertently state-of-the-art in knowledge-based {WSD}",
    author = "Agirre, Eneko  and
      L{\'o}pez de Lacalle, Oier  and
      Soroa, Aitor",
    editor = "Park, Eunjeong L.  and
      Hagiwara, Masato  and
      Milajevs, Dmitrijs  and
      Tan, Liling",
    booktitle = "Proceedings of Workshop for {NLP} Open Source Software ({NLP}-{OSS})",
    month = jul,
    year = "2018",
    address = "Melbourne, Australia",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/W18-2505/",
    doi = "10.18653/v1/W18-2505",
    pages = "29--33",
    abstract = "UKB is an open source collection of programs for performing, among other tasks, Knowledge-Based Word Sense Disambiguation (WSD). Since it was released in 2009 it has been often used out-of-the-box in sub-optimal settings. We show that nine years later it is the state-of-the-art on knowledge-based WSD. This case shows the pitfalls of releasing open source NLP software without optimal default settings and precise instructions for reproducibility."
}