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--- |
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tags: |
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- feature-extraction |
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- endpoints-template |
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license: bsd-3-clause |
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library_name: generic |
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--- |
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# Coreference Resolution for Long Documents |
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Modified coreference resolution model from [BERT for Coreference Resolution: Baselines and Analysis](https://aclanthology.org/D19-1588/) for handling long documents (~40K words) efficiently (500K words/s on a NVIDIA Tesla V100). The checkpoint is based on AllenNLP's coref-spanbert-large-2021.03.10. This modified model was used in [DAPR: A Benchmark on Document-Aware Passage Retrieval](https://arxiv.org/abs/2305.13915). |
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## Usage |
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### API call |
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One can call the Hugging's Inference Endpoints API directly: (need your access token from https://huggingface.co/settings/tokens and the loading takes around 6 minutes) |
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```python |
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import requests |
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import time |
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API_URL = "https://api-inference.huggingface.co/models/kwang2049/long-coref" |
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headers = {"Authorization": "Bearer ${YOUR_HUGGINGFACE_ACCESS_TOKEN}"} |
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def query(payload): |
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while True: |
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response = requests.post(API_URL, headers=headers, json=payload) |
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if response.status_code == 503: |
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time.sleep(5) |
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print(response.json()["error"]) |
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continue |
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elif response.status_code == 200: |
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return response.json() |
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else: |
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error_message = f"{response.status_code}: {response.json['error']}." |
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raise requests.HTTPError(error_message) |
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doc = [ |
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"The Half Moon is a public house and music venue in Putney, London. It is one of the city's longest running live music venues, and has hosted live music every night since 1963.", |
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"The pub is on the south side of the Lower Richmond road, in the London Borough of Wandsworth." |
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] |
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PARAGRAPH_DELIMITER = "\n\n" |
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output = query( |
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{ |
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"inputs": PARAGRAPH_DELIMITER.join(doc), |
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} |
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) |
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print(output) |
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# { |
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# 'pargraph_sentences': ..., |
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# 'top_spans': ..., |
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# 'antecedents': ... |
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# } |
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``` |
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### Local run |
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One can also run the code of the repo on a local machine: |
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```bash |
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# Clone the repo |
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git lfs install |
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git clone https://huggingface.co/kwang2049/long-coref |
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cd long-coref |
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pip install -r requirements.txt |
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python local_run.py |
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``` |
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## Evalution |
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The evaluation results on OntoNotesv5 are: |
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| Model | Precision | Recall | F1 | Input Length| |
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| --- | --- | --- | --- | --- | |
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| AllenNLP's original implementation | 79.2 | 78.4 | 78.8 | <= 2K words| |
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| This modification | 78.9 | 67.0 | 72.4| <= 40K words | |
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## Citation |
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If you use the repo, feel free to cite our publication [DAPR: A Benchmark on Document-Aware Passage Retrieval](https://arxiv.org/abs/2305.13915): |
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```bibtex |
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@article{wang2023dapr, |
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title = "DAPR: A Benchmark on Document-Aware Passage Retrieval", |
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author = "Kexin Wang and Nils Reimers and Iryna Gurevych", |
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journal= "arXiv preprint arXiv:2305.13915", |
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year = "2023", |
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url = "https://arxiv.org/abs/2305.13915", |
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} |
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``` |
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