README.md

metadata

license: cc-by-4.0
language:
  - en
tags:
  - ambiguity
  - relatedness
  - language
pretty_name: Relatedness of Ambiguous Words in Context

RAW-C: Relatedness of Ambiguous Words in Context

RAW-C contains relatedness judgments about ambiguous words in minimal pair contexts, e.g.,
"She liked the marinated lamb" vs. "She liked the friendly lamb".
The dataset was originally published in ACL 2021.

• 672 sentence pairs total
• 112 words (2 senses each, 2 sentences per sense)
• Annotated for Same vs. Different Sense, and for Polysemy vs. Homonymy
• Crowd-sourced relatedness judgments

Dataset Format

Main file: raw-c.csv
Key columns:

• word: Target word
• sentence1, sentence2: The sentence pair being contrasted
• same: Whether the target word has the same or different meaning across sentences
• ambiguity_type: Polysemy or Homonymy
• mean_relatedness: Mean relatedness score across human participants
• string: The actual surface form of the word in context
• count: Number of annotators
• sd_relatedness: Standard deviation of human ratings
• dominance_sentence2: Mean dominance of sentence 2 relative to sentence 1
• sd_dominance_sentence2: Standard deviation of dominance ratings

Dominance ratings are included only for Different Sense pairs.

Citation

If you use RAW-C in your research, please cite:

APA:
Trott, S., & Bergen, B. (2021). RAW-C: Relatedness of Ambiguous Words in Context (A New Lexical Resource for English).
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (ACL-IJCNLP 2021).

BibTeX:

@inproceedings{trott-bergen-2021-raw,
  title = "{RAW}-{C}: Relatedness of Ambiguous Words in Context (A New Lexical Resource for {E}nglish)",
  author = "Trott, Sean  and Bergen, Benjamin",
  booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
  year = "2021",
  publisher = "Association for Computational Linguistics",
  url = "https://aclanthology.org/2021.acl-long.550/",
  doi = "10.18653/v1/2021.acl-long.550",
  pages = "7077--7087"
}