@inproceedings{colson-2020-extracting,
    title = "Extracting meaning by idiomaticity: Description of the {HS}em{ID} system at {C}og{AL}ex {VI} (2020)",
    author = "Colson, Jean-Pierre",
    editor = "Zock, Michael  and
      Chersoni, Emmanuele  and
      Lenci, Alessandro  and
      Santus, Enrico",
    booktitle = "Proceedings of the Workshop on the Cognitive Aspects of the Lexicon",
    month = dec,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.cogalex-1.6/",
    pages = "54--58",
    abstract = "The HSemID system, submitted to the CogALex VI Shared Task is a hybrid system relying mainly on metric clusters measured in large web corpora, complemented by a vector space model using cosine similarity to detect semantic associations. Although the system reached ra-ther weak results for the subcategories of synonyms, antonyms and hypernyms, with some dif-ferences from one language to another, it is able to measure general semantic associations (as being random or not-random) with an F1 score close to 0.80. The results strongly suggest that idiomatic constructions play a fundamental role in semantic associations. Further experiments are necessary in order to fine-tune the model to the subcategories of synonyms, antonyms, hy-pernyms and to explain surprising differences across languages. 1 Introduction"
}