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 ---
-license: apache-2.0
+license: cc
 language:
 - it
 pretty_name: SubCat
----
+---
+
+
+# SubCat: A Dataset of Subordinate Categories in Human Mind and LLMs for the Italian Language
+<div align="center">
+<!-- <img src="assets/subCat.png"  height="400" width="auto" style="border-radius:3%" /> -->
+<img src="assets/image_qwen_subcat_1.webp"  height="400" width="auto" style="border-radius:3%" />
+</div>
+
+A psycholinguistic italian dataset released with the paper <a href="https://aclanthology.org/2025.acl-long.224/">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.
+
+## Dataset Creation
+
+The 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).
+
+An 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.
+
+
+The final human dataset, after cleaning and standardization, consists of 24,659 exemplars.
+
+## Data Processing
+
+Raw 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.
+
+
+### Dataset Description
+
+- **Curated by:** [ABSTRACTION-ERC Team](https://site.unibo.it/abstraction/it) of the University of Bologna, and the [AI4Text Group](https://hlt-isti.github.io/) at CNR-ISTI
+- **Language(s) (NLP):** Italian 
+- **License:** CC BY 4.0
+
+## Dataset Structure
+
+The 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:
+
+1. `category`: the super-ordinate category
+2. `concept`: the basic-level category
+3. `exemplar`: the generated/produced sub-ordinate level exemplar/concept
+4. `exemplar_string`: a sanitized version of the exemplar
+5. `availability`: a metric which represents how readily the exemplar is produced as a member of its associated category
+6. `count`: the number of occurrences of the exemplar across participants
+7. `min_rank`: the minimum rank of exemplar's occurrence
+8. `max_rank`: the highest rank of exemplar's occurrence
+9. `mean_rank`: the average rank of exemplar's occurrence
+10. `first_occur`: the ratio of exemplar occurring at first rank, divided by the total number of exemplar's occurrence
+11. `dominance`: the proportion of participants who produce the exemplar given its associated category
+12. `abs_freq_corpus`: only for LLM's generated exemplars, the number of exemplar's occurrences in the italian corpus `ItTenTen`
+
+
+## Citation
+
+<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
+If you find this dataset is useful in your own work, please consider citing it as follows:
+
+```
+@inproceedings{pedrotti-etal-2025-humans,
+    title = "How Humans and {LLM}s Organize Conceptual Knowledge: Exploring Subordinate Categories in {I}talian",
+    author = "Pedrotti, Andrea  and
+      Rambelli, Giulia  and
+      Villani, Caterina  and
+      Bolognesi, Marianna",
+    editor = "Che, Wanxiang  and
+      Nabende, Joyce  and
+      Shutova, Ekaterina  and
+      Pilehvar, Mohammad Taher",
+    booktitle = "Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
+    month = jul,
+    year = "2025",
+    address = "Vienna, Austria",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2025.acl-long.224/",
+    doi = "10.18653/v1/2025.acl-long.224",
+    pages = "4464--4482",
+    ISBN = "979-8-89176-251-0",
+}
+```