Add dataset card

README.md

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+---
+license: cc-by-nc-4.0
+language:
+- fa
+pretty_name: PerSHOP
+size_categories:
+- 10K<n<100K
+task_categories:
+- text-classification
+- token-classification
+- text-generation
+task_ids:
+- intent-classification
+- named-entity-recognition
+- dialogue-modeling
+tags:
+- task-oriented-dialogue
+- shopping
+- persian
+- dialogue-state-tracking
+- slot-filling
+configs:
+- config_name: dialogues
+  default: true
+  data_files:
+  - split: train
+    path: data/dialogues/train.jsonl
+  - split: validation
+    path: data/dialogues/validation.jsonl
+  - split: test
+    path: data/dialogues/test.jsonl
+- config_name: products
+  data_files:
+  - split: database
+    path: data/products/products.jsonl
+- config_name: slots
+  data_files:
+  - split: descriptions
+    path: data/products/slots.jsonl
+---
+
+# PerSHOP: A Multi-Domain Persian Dataset for Shopping Dialogue Systems
+
+PerSHOP is a Persian task-oriented dialogue dataset in the shopping domain. Each
+dialogue is a conversation between a customer and a seller who fill a shopping
+basket from a fixed product database. Utterances are annotated with domain,
+intent/dialogue act, product category and inline slot spans.
+
+This is the **official release** maintained by the authors, with fixed
+dialogue-level train/validation/test splits and the product database used to
+collect the dialogues.
+
+| | |
+|---|---|
+| Dialogues | 1,061 |
+| Utterances | 21,923 |
+| Domains | 14 product domains + chit-chat |
+| Intents / dialogue acts | 20 |
+| Slot types | 27 |
+| Products in the database | 750 |
+| Mean utterances per dialogue | 20.7 |
+
+## Collection
+
+The dialogues were collected at the University of Tehran through a web platform
+built for this purpose. About 120 volunteer students (out of roughly 340 enrolled
+in the Data Structures and Natural Language Processing courses over three
+semesters) took the customer and seller roles and conducted shopping
+conversations over a shared product database, following a written guideline.
+The dialogues were then annotated by the first author.
+
+The conversations are role-played; the released data contains only the speaker
+role (`user` or `system`) and no identifiers of the participants.
+
+## Splits
+
+| Split | Dialogues | Utterances |
+|---|---|---|
+| train | 849 | 17,482 |
+| validation | 106 | 2,242 |
+| test | 106 | 2,199 |
+
+* The split is made at the **dialogue level**: all utterances of a dialogue are
+  in the same split, so no dialogue context leaks into evaluation data.
+* 80/10/10, stratified by each dialogue's primary domain (its most frequent
+  product domain), with a fixed seed (42).
+* The dialogue IDs of each split are listed in `splits/`, and
+  `scripts/make_splits.py` rebuilds the release exactly from the original
+  spreadsheets.
+
+Please report results on the `test` split and use `validation` for model
+selection.
+
+## Data fields
+
+### `dialogues` (one row per utterance)
+
+| Field | Description |
+|---|---|
+| `utterance_id` | Utterance ID from the original release (unique; IDs are not contiguous) |
+| `dialogue_id` | Dialogue ID (1–1061) |
+| `turn_index` | Position of the utterance within its dialogue, from 0 |
+| `speaker` | `user` (customer) or `system` (seller) |
+| `domain` | Domain in Persian, as annotated (`Chats` for chit-chat turns) |
+| `domain_en` | English name of the domain |
+| `intent` | Intent or dialogue act, e.g. `Purchase`, `Inform`, `Ask_slot`, `Ask_product`, `Add_product` |
+| `super_product` | Product category the turn is about, e.g. `milk`, `water` (null for chit-chat) |
+| `text` | Utterance text with annotation markup removed |
+| `annotated_text` | Annotated utterance; slots are marked inline as `[span](slot)` (see Corrections) |
+| `raw_text` | `RawText` column of the original release, kept unchanged |
+| `entities` | Slot spans parsed from `annotated_text`: `value`, `slot`, and `start`/`end` character offsets in `text` |
+
+### `products`
+
+The product database (750 items). Each record has `id`, `full_name`, `domain`,
+`domain_en`, `super_product`, `product`, `price` and the attribute slots that
+apply to that product (e.g. `brand`, `flavor`, `volume`, `weight`, `fat`).
+
+### `slots`
+
+Names and English descriptions of the product attribute slots.
+
+## Usage
+
+```python
+from datasets import load_dataset
+
+dialogues = load_dataset("KeyvanMahmoudi/PerSHOP", "dialogues")
+products = load_dataset("KeyvanMahmoudi/PerSHOP", "products", split="database")
+```
+
+## Corrections
+
+Compared with the original spreadsheet, this release applies a small set of
+documented corrections, listed in `scripts/corrections.json`:
+
+* 13 utterances had slot markup that could not be parsed (e.g. `(volume)[1.5]`,
+  a missing bracket, or a missing slot label). Their syntax was fixed so the
+  annotated spans are recoverable; in two of them (`utterance_id` 7835 and
+  7879) the `product` and `bag_number` labels had been attached to the wrong
+  spans and were swapped back.
+* 2 empty user utterances (`utterance_id` 12536 and 13069) were removed.
+* The slot `super-product` was renamed `super_product`, matching the naming of
+  all other slots.
+
+`raw_text` is unchanged. In 242 cases an utterance follows another utterance by
+the same speaker within a dialogue; these are kept as collected.
+
+## License
+
+The dataset (dialogues, annotations and product database) is released under the
+[Creative Commons Attribution-NonCommercial 4.0 International](https://creativecommons.org/licenses/by-nc/4.0/)
+license. Research and other non-commercial use is permitted with citation of the
+paper below.
+
+**Commercial use** — including training, fine-tuning or deploying models for
+commercial products or services — is not covered by this license and requires a
+separate written agreement with the authors.
+
+Copies of PerSHOP published by third parties are not maintained by the authors;
+this license applies to all copies.
+
+## Citation
+
+```bibtex
+@inproceedings{mahmoudi2026pershop,
+  title     = {PerSHOP: A Multi-Domain Persian Dataset for Shopping Dialogue Systems},
+  author    = {Mahmoudi, Keyvan and Faili, Heshaam},
+  booktitle = {2026 International Interdisciplinary Conference on Artificial Intelligence: Engineering, Health, Finance and Humanities (IICAI)},
+  pages     = {1--6},
+  year      = {2026},
+  address   = {Tehran, Iran},
+  doi       = {10.1109/IICAI70155.2026.11620935}
+}
+
+@article{mahmoudi2024pershop,
+  title   = {PerSHOP -- A Persian dataset for shopping dialogue systems modeling},
+  author  = {Mahmoudi, Keyvan and Faili, Heshaam},
+  journal = {arXiv preprint arXiv:2401.00811},
+  year    = {2024}
+}
+```
+
+## Links
+
+* Paper (IEEE): https://doi.org/10.1109/IICAI70155.2026.11620935
+* Preprint: https://arxiv.org/abs/2401.00811
+* Code and original files: https://github.com/keyvanmahmoudi/PerSHOP