HuWiC

Data and algorithms of the creation process of the Hungarian Word-in-Context Corpus

Data

Data folder contains the important outputs of the project so far

Bin

Bin folder contains the codes of the project so far

Citation Information

If you use this resource or any part of its documentation, please refer to:

A Clique-based Graphical Approach to Detect Interpretable Adjectival Senses in Hungarian (Héja & Ligeti-Nagy, TextGraphs 2022)

@inproceedings{heja-ligeti-nagy-2022-clique,
    title = "A Clique-based Graphical Approach to Detect Interpretable Adjectival Senses in {H}ungarian",
    author = "H{\'e}ja, Enik{\H{o}}  and
      Ligeti-Nagy, No{\'e}mi",
    booktitle = "Proceedings of TextGraphs-16: Graph-based Methods for Natural Language Processing",
    month = oct,
    year = "2022",
    address = "Gyeongju, Republic of Korea",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.textgraphs-1.4",
    pages = "35--43",
    abstract = "The present paper introduces an ongoing research which aims to detect interpretable adjectival senses from monolingual corpora applying an unsupervised WSI approach. According to our expectations the findings of our investigation are going to contribute to the work of lexicographers, linguists and also facilitate the creation of benchmarks with semantic information for the NLP community. For doing so, we set up four criteria to distinguish between senses. We experiment with a graphical approach to model our criteria and then perform a detailed, linguistically motivated manual evaluation of the results."
}