LT3/different_definitions_annotations

23 downloads in 30 days0 likesLast modified 8 Aug 2025View on Hugging Face

The declared licence (mit) is classified as permissive.

Declared licence: mit, from the tagEvidence: README.md at 1788f40
Licence files: No licence file at the top level of the repositoryEvidence: file list at 1788f40
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Citation text from the card

If you would like to use or cite this dataset, feel free to use the following BibTeX code:

```bibtex
@inproceedings{evgrafova-etal-2025-stance,
    title = "Stance-aware Definition Generation for Argumentative Texts",
    author = "Evgrafova, Natalia  and
      De Langhe, Loic
and
 Hoste, Veronique and
      Lefever, Els  ",
    editor = "Chistova, Elena  and
      Cimiano, Philipp  and
      Haddadan, Shohreh  and
      Lapesa, Gabriella  and
      Ruiz-Dolz, Ramon",
    booktitle = "Proceedings of the 12th Argument mining Workshop",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.argmining-1.16/",
    doi = "10.18653/v1/2025.argmining-1.16",
    pages = "168--180",
    ISBN = "979-8-89176-258-9",
    abstract = "Definition generation models trained on dictionary data are generally expected to produce neutral and unbiased output while capturing the contextual nuances. However, previous studies have shown that generated definitions can inherit biases from both the underlying models and the input context. This paper examines the extent to which stance-related bias in argumentative data influences the generated definitions. In particular, we train a model on a slang-based dictionary to explore the feasibility of generating persuasive definitions that concisely reflect opposing parties' understandings of contested terms. Through this study, we provide new i

All datasets marked Permissive or share-alike | JSON

The same facts for your agent

A free MCP server at mcp.datalicense.uk/mcp. Connect it from an MCP client such as Claude or Cursor.

dataset_licence({ "id": "LT3/different_definitions_annotations" })
signal: "permissive"
stated_licence: "mit"
sources: 0