ABSTRACTION-ERC/subCat-human

1---2license: cc3language:4- it5pretty_name: SubCat6---7 8 9# SubCat: A Dataset of Subordinate Categories in Human Mind and LLMs for the Italian Language10<div align="center">11<!-- <img src="assets/subCat.png"  height="400" width="auto" style="border-radius:3%" /> -->12<img src="assets/subCat_2.png"  height="400" width="auto" style="border-radius:3%" />13</div>14 15A psycholinguistic italian dataset released with the paper <a href="https://arxiv.org/abs/2505.21301">How Humans and LLMs Organize Conceptual Knowledge: Exploring Subordinate Categories in Italian</a>. It contains a list of subordiante categories, or exemplars, for 187 concrete words or, basic-level categories.16 17## Dataset Creation18 19The dataset was created to study how Italian L1 speakers generate exemplars for common object categories. The stimuli consisted of 187 basic-level concrete categories (e.g., dog, table) organized under 12 superordinate semantic categories (e.g., animals, furniture).20 21An exemplar generation task was administered to 365 Italian L1 speakers. Participants were presented with a list of 15-16 categories and asked to produce as many exemplars as possible for each concept at their own pace.22 23 24The final human dataset, after cleaning and standardization, consists of 24,659 exemplars.25 26## Data Processing27 28Raw data underwent a post-processing step to correct common typos and misspellings. This was done to ensure the consistency and accuracy of the final dataset. The corrected exemplars were then standardized to a common format.29 30 31## Dataset Description32 33- **Curated by:** [ABSTRACTION-ERC Team](https://site.unibo.it/abstraction/it)34- **Curated by:** [AI4Text Group](https://hlt-isti.github.io/)35- **Language(s) (NLP):** Italian 36- **License:** CC BY 4.037 38## Dataset Structure39 40The dataset contains the aggregated results of the human experiment. For row in the dataset contains a unique subordinate exemplars and related statistics. The dataset contains the following columns:41 421. `category`: the super-ordinate category432. `concept`: the basic-level category443. `exemplar`: the generated/produced sub-ordinate level exemplar/concept454. `exemplar_string`: a sanitized version of the exemplar465. `availability`: a metric which represents how readily the exemplar is produced as a member of its associated category476. `count`: the number of occurrences of the exemplar across participants487. `min_rank`: the minimum rank of exemplar's occurrence498. `max_rank`: the highest rank of exemplar's occurrence509. `mean_rank`: the average rank of exemplar's occurrence5110. `first_occur`: the ratio of exemplar occurring at first rank, divided by the total number of exemplar's occurrence5211. `dominance`: the proportion of participants who produce the exemplar given its associated category5312. `abs_freq_corpus`: only for LLM's generated exemplars, the number of exemplar's occurrences in the italian corpus `ItTenTen`54 55 56## Citation57 58<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->59If you find this dataset is useful in your own work, please consider citing it as follows:60 61```62@inproceedings{pedrotti-etal-2025-humans,63    title = "How Humans and {LLM}s Organize Conceptual Knowledge: Exploring Subordinate Categories in {I}talian",64    author = "Pedrotti, Andrea  and65      Rambelli, Giulia  and66      Villani, Caterina  and67      Bolognesi, Marianna",68    editor = "Che, Wanxiang  and69      Nabende, Joyce  and70      Shutova, Ekaterina  and71      Pilehvar, Mohammad Taher",72    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",73    month = jul,74    year = "2025",75    address = "Vienna, Austria",76    publisher = "Association for Computational Linguistics",77    url = "https://aclanthology.org/2025.acl-long.224/",78    doi = "10.18653/v1/2025.acl-long.224",79    pages = "4464--4482",80    ISBN = "979-8-89176-251-0",81}82```