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--- |
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title: Perin |
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emoji: 📊 |
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colorFrom: purple |
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colorTo: green |
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sdk: gradio |
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sdk_version: 3.1.7 |
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app_file: app.py |
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pinned: false |
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--- |
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This space provides a gradio demo and an easy-to-run wrapper of the pre-trained model for structured sentiment analysis in Norwegian language, pre-trained on the [NoReC dataset](https://huggingface.co/datasets/norec). |
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This model is an implementation of the paper "Direct parsing to sentiment graphs" (Samuel _et al._, ACL 2022). The main repository that also contains the scripts for training the model, can be found on the project [github](https://github.com/jerbarnes/direct_parsing_to_sent_graph). |
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The current model uses the 'labeled-edge' graph encoding, and achieves the following results on the NoReC dataset: |
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| Unlabeled sentiment tuple F1 | Target F1 | Relative polarity precision | |
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|:----------------------------:|:----------:|:---------------------------:| |
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| 0.393 | 0.468 | 0.939 | |
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The model can be easily used for predicting sentiment tuples as follows: |
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```python |
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>>> import model_wrapper |
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>>> model = model_wrapper.PredictionModel() |
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>>> model.predict(['vi liker svart kaffe']) |
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[{'sent_id': '0', |
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'text': 'vi liker svart kaffe', |
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'opinions': [{'Source': [['vi'], ['0:2']], |
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'Target': [['svart', 'kaffe'], ['9:14', '15:20']], |
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'Polar_expression': [['liker'], ['3:8']], |
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'Polarity': 'Positive'}]}] |
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``` |
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