There and Back Again: Cross-Lingual Transfer Learning for Event Detection

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    Abstract

    In this contribution we in- vestigate the generalisation abilities of a pre-trained multilingual Language Model, namely Multilingual BERT, in different transfer learning scenarios for event de- tection and classification for Italian and English. Our results show that zero-shot models have satisfying, although not opti- mal, performances in both languages (av- erage F1 higher than 60 for event detec- tion vs. average F1 ranging between 40 and 50 for event classification). We also show that adding extra fine-tuning data of the evaluation language is not simply ben- eficial but results in better models when compared to the corresponding non zero- shot transfer ones, achieving highly com- petitive results when compared to state-of-
    the-art systems.
    Original languageEnglish
    Title of host publicationProceedings of the Sixth Italian Conference on Computational Linguistics
    PublisherCEUR Workshop Proceedings (CEUR-WS.org)
    Volume2481
    Publication statusPublished - 2019

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