58 lines
1.9 KiB
Markdown
58 lines
1.9 KiB
Markdown
# Automatic Term Extraction API
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## 1. Description
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In this repo, we wrote an API to inference SloBERTa term extractor, whose model has been trained with [RSDO5 corpus](https://www.clarin.si/repository/xmlui/handle/11356/1400). Feel free to check out this [repo](https://github.com/honghanhh/ate-2022) for better understanding about the methodology.
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---
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## 2. Requirements
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Please install all the necessary libraries noted in [requirements.txt](./requirements.txt) using this command:
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```
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pip install -r requirements.txt
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```
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## 3. Implementation
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Download the model from [pytorch_model.bin](https://kt-cloud.ijs.si/index.php/s/T4qtSKxbxgqr6c5) and save it into `./model/term_extractor/`.
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Run the following command on the terminal:
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```python
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main.py
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```
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A link will be show on the terminal so that you can access to the API and test requests.
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```python
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* Serving Flask app 'main'
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* Debug mode: on
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WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
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* Running on http://127.0.0.1:5000
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Press CTRL+C to quit
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* Restarting with stat
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* Debugger is active!
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* Debugger PIN: 185-520-689
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```
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We suggest you use POSTMAN or Hoppscotch to test the API with an uploaded file as the output whose format is CONLL-like (plese check out [temp_1.conllu](temp_1.conllu)). See the demonstration as the image below.
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## 4. Docker version
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Run the following command:
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```python
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docker build -t ate .
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docker run -d -p 5000:5000 ate
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```
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## 5. References
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The term extraction tool is an updated version of Tran et al. (2022), using the SloBERTa model.
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Hanh Thi Hong Tran, Matej Martinc, Andraz Repar, Antoine Doucet and Senja Pollak: A Transformer-based Sequence-labeling Approach to the Slovenian Cross-domain Automatic Term Extraction. Proc. of Jezikovne tehnologije in digitalna humanistika, 2022.
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## 6. Contributors:
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- 🐮 [TRAN Thi Hong Hanh](https://github.com/honghanhh) 🐮
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- Matej Martinc
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- Senja Pollak
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