E2E-TBSA

Source code of our AAAI paper on End-to-End Target/Aspect-Based Sentiment Analysis.

Requirements

• Python 3.6
• DyNet 2.0.2 (For building DyNet and enabling the python bindings, please follow the instructions in this link)
• nltk 3.2.2
• numpy 1.13.3

Data

• rest_total consist of the reviews from the SemEval-2014, SemEval-2015, SemEval-2016 restaurant datasets.
• laptop14 is identical to the SemEval-2014 laptop dataset.
• twitter is built by Mitchell et al. (EMNLP 2013).
• We also provide the data in the format of conll03 NER dataset.

Parameter Settings

• To reproduce the results, please refer to the settings in config.py.

Environment

• OS: REHL Server 6.4 (Santiago)
• CPU: Intel Xeon CPU E5-2620 (Yes, we do not use GPU to gurantee the deterministic outputs)

Citation

If the code is used in your research, please star this repo and cite our paper as follows:

@inproceedings{li2019unified,
  title={A unified model for opinion target extraction and target sentiment prediction},
  author={Li, Xin and Bing, Lidong and Li, Piji and Lam, Wai},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  pages={6714--6721},
  year={2019}
}