Generationary

A generative dictionary approach to lexical semantics.

Welcome to the page of Generationary, a project of the Sapienza NLP Group, developed with the support of the awesome MOUSSE ERC project!

Generationary is a neural seq2seq model which contextualizes a target expression in a sentence by generating an ad hoc definition.

Our work is a unified approach to computational lexical-semantic tasks, encompassing state-of-the-art Word Sense Disambiguation, Definition Modeling and Word-in-Context.

To learn more, read our paper:

Michele Bevilacqua, Marco Maru, and Roberto Navigli. 2020. Generationary or: “How We Went beyond Sense Inventories and Learned to Gloss”. Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP).

Data and Software

Download Hei++ and SamplEval here.

The code is available on request (you can contact us at bevilacqua [at] di [dot] uniroma1 [dot] it or marco [dot] maru [at] uniroma1 [dot] it).

Reference

@inproceedings{bevilacqua-etal-2020-generationary,
    title = "Generationary or: {``}How We Went beyond Word Sense Inventories and Learned to Gloss{''}",
    author = "Bevilacqua, Michele  and
      Maru, Marco  and
      Navigli, Roberto",
    booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)",
    month = nov,
    year = "2020",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/2020.emnlp-main.585",
    pages = "7207--7221",
}

Authors

Acknowledgements

The authors gratefully acknowledge the support of the ERC Consolidator Grant MOUSSE No. 726487 under the European Union’s Horizon 2020 research and innovation programme.