| --- |
| license: |
| - cc-by-nc-sa-4.0 |
| source_datasets: |
| - original |
| task_ids: |
| - word-sense-disambiguation |
| pretty_name: word-sense-linking-dataset |
| tags: |
| - word-sense-linking |
| - word-sense-disambiguation |
| - lexical-semantics |
| size_categories: |
| - 10K<n<100K |
| datasets: |
| - Babelscape/wsl |
| language: |
| - en |
| --- |
| --- |
|
|
|
|
| # Word Sense Linking: Disambiguating Outside the Sandbox |
|
|
| [](https://2024.aclweb.org/) |
| [](https://aclanthology.org/2024.findings-acl.851/) |
| [](https://huggingface.co/collections/Babelscape/word-sense-linking-66ace2182bc45680964cefcb) |
| [](https://github.com/Babelscape/WSL) |
|
|
| ## Model Description |
|
|
|
|
| We introduce the task of Word Sense Linking (WSL), which focuses on accurately mapping spans of text to their most appropriate senses using a reference inventory. The Word Sense Linking model is designed to identify and disambiguate spans of text to their most suitable senses from a reference inventory. The annotations are provided as sense keys from WordNet, a large lexical database of English. |
|
|
| ## Installation |
|
|
| Installation from PyPI: |
|
|
| ```bash |
| git clone https://github.com/Babelscape/WSL |
| cd WSL |
| pip install -r requirements.txt |
| ``` |
|
|
|
|
|
|
| ## Usage |
|
|
| WSL is composed of two main components: a retriever and a reader. |
| The retriever is responsible for retrieving relevant senses from a senses inventory (e.g WordNet), |
| while the reader is responsible for extracting spans from the input text and link them to the retrieved documents. |
| WSL can be used with the `from_pretrained` method to load a pre-trained pipeline. |
|
|
| ```python |
| from wsl import WSL |
| from wsl.inference.data.objects import WSLOutput |
| |
| wsl_model = WSL.from_pretrained("Babelscape/wsl-base") |
| wsl_out: WSLOutput = wsl_model("Bus drivers drive busses for a living.") |
| ``` |
|
|
| WSLOutput( |
| text='Bus drivers drive busses for a living.', |
| tokens=['Bus', 'drivers', 'drive', 'busses', 'for', 'a', 'living', '.'], |
| id=0, |
| spans=[ |
| Span(start=0, end=11, label='bus driver: someone who drives a bus', text='Bus drivers'), |
| Span(start=12, end=17, label='drive: operate or control a vehicle', text='drive'), |
| Span(start=18, end=24, label='bus: a vehicle carrying many passengers; used for public transport', text='busses'), |
| Span(start=31, end=37, label='living: the financial means whereby one lives', text='living') |
| ], |
| candidates=Candidates( |
| candidates=[ |
| {"text": "bus driver: someone who drives a bus", "id": "bus_driver%1:18:00::", "metadata": {}}, |
| {"text": "driver: the operator of a motor vehicle", "id": "driver%1:18:00::", "metadata": {}}, |
| {"text": "driver: someone who drives animals that pull a vehicle", "id": "driver%1:18:02::", "metadata": {}}, |
| {"text": "bus: a vehicle carrying many passengers; used for public transport", "id": "bus%1:06:00::", "metadata": {}}, |
| {"text": "living: the financial means whereby one lives", "id": "living%1:26:00::", "metadata": {}} |
| ] |
| ), |
| ) |
| |
|
|
|
|
| ## Model Performance |
|
|
| Here you can find the performances of our model on the [WSL evaluation dataset](https://huggingface.co/datasets/Babelscape/wsl). |
|
|
| ### Validation (SE07) |
|
|
| | Models | P | R | F1 | |
| |--------------|------|--------|--------| |
| | BEM_SUP | 67.6 | 40.9 | 51.0 | |
| | BEM_HEU | 70.8 | 51.2 | 59.4 | |
| | ConSeC_SUP | 76.4 | 46.5 | 57.8 | |
| | ConSeC_HEU | **76.7** | 55.4 | 64.3 | |
| | **Our Model**| 73.8 | **74.9** | **74.4** | |
|
|
| ### Test (ALL_FULL) |
| |
| | Models | P | R | F1 | |
| |--------------|------|--------|--------| |
| | BEM_SUP | 74.8 | 50.7 | 60.4 | |
| | BEM_HEU | 76.6 | 61.2 | 68.0 | |
| | ConSeC_SUP | 78.9 | 53.1 | 63.5 | |
| | ConSeC_HEU | **80.4** | 64.3 | 71.5 | |
| | **Our Model**| 75.2 | **76.7** | **75.9** | |
| |
| |
| |
| ## Additional Information |
| **Licensing Information**: Contents of this repository are restricted to only non-commercial research purposes under the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License (CC BY-NC-SA 4.0)](https://creativecommons.org/licenses/by-nc-sa/4.0/). Copyright of the dataset contents belongs to Babelscape. |
| **Arxiv Paper:** [Word Sense Linking: Disambiguating Outside the Sandbox](https://arxiv.org/abs/2412.09370) |
| |
| ## Citation Information |
| |
| |
| ```bibtex |
| @inproceedings{bejgu-etal-2024-wsl, |
| title = "Word Sense Linking: Disambiguating Outside the Sandbox", |
| author = "Bejgu, Andrei Stefan and Barba, Edoardo and Procopio, Luigi and Fern{\'a}ndez-Castro, Alberte and Navigli, Roberto", |
| booktitle = "Findings of the Association for Computational Linguistics: ACL 2024", |
| month = aug, |
| year = "2024", |
| address = "Bangkok, Thailand", |
| publisher = "Association for Computational Linguistics", |
| } |
| ``` |
| |
| **Contributions**: Thanks to [@andreim14](https://github.com/andreim14), [@edobobo](https://github.com/edobobo), [@poccio](https://github.com/poccio) and [@navigli](https://github.com/navigli) for adding this model. |
