README.md

metadata

license: cc-by-4.0
language:
  - es
tags:
  - language
  - ambiguity
  - relatedness
pretty_name: Spanish Ambiguous Words in Context
size_categories:
  - n<1K

SAW-C: Spanish Ambiguous Words—in Context

SAW-C contains relatedness judgments about Spanish 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 NAACL 2025.

• 102 words.
• 812 sentence pairs (average of 28 per word).
• Annotated for Same vs. Different Sense.
• Crowd-sourced relatedness judgments.

Dataset Format

Main file: saw-c.csv
Key columns:

• Word: Target word
• Sentence_1, Sentence_2: Sentence pair being contrasted
• Gender_s1, Gender_s2: Grammatical gender of target word in each sentence
• mean_relatedness: Mean relatedness score across human participants
• sd_relatedness: Standard deviation of human ratings
• count: Number of annotators

Citation

APA:

Rivière, P. D., Beatty-Martínez, A. L., & Trott, S. (2025). Evaluating Contextualized Representations of (Spanish) Ambiguous Words: A New Lexical Resource and Empirical Analysis. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) (pp. 8322–8338). https://aclanthology.org/2025.naacl-long.422/

Citation (BibTex):

@inproceedings{riviere-etal-2025-evaluating,
    title = "Evaluating Contextualized Representations of ({S}panish) Ambiguous Words: A New Lexical Resource and Empirical Analysis",
    author = "Riviere, Pamela D  and
      Beatty-Mart{\'i}nez, Anne L.  and
      Trott, Sean",
    editor = "Chiruzzo, Luis  and
      Ritter, Alan  and
      Wang, Lu",
    booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
    month = apr,
    year = "2025",
    address = "Albuquerque, New Mexico",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.naacl-long.422/",
    pages = "8322--8338",
    ISBN = "979-8-89176-189-6",
    abstract = "Lexical ambiguity{---}where a single wordform takes on distinct, context-dependent meanings{--}serves as a useful tool to compare across different language models' (LMs') ability to form distinct, contextualized representations of the same stimulus. Few studies have systematically compared LMs' contextualized word embeddings for languages beyond English. Here, we evaluate semantic representations of Spanish ambiguous nouns in context in a suite of Spanish-language monolingual and multilingual BERT-based models. We develop a novel dataset of minimal-pair sentences evoking the same or different sense for a target ambiguous noun. In a pre-registered study, we collect contextualized human relatedness judgments for each sentence pair. We find that various BERT-based LMs' contextualized semantic representations capture some variance in human judgments but fall short of the human benchmark. In exploratory work, we find that performance scales with model size. We also identify stereotyped trajectories of target noun disambiguation as a proportion of traversal through a given LM family`s architecture, which we partially replicate in English. We contribute (1) a dataset of controlled, Spanish sentence stimuli with human relatedness norms, and (2) to our evolving understanding of the impact that LM specification (architectures, training protocols) exerts on contextualized embeddings."
}