A sample pytorch Implementation of ACL 2021 research paper "Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction".

Span-ASTE-Pytorch

This repository is a pytorch version that implements Ali's ACL 2021 research paper Learning Span-Level Interactions for Aspect Sentiment Triplet Extraction .

• 🤗 The original repository of the paper is based on the allennlp implementation
• 🤗 Thanks to Ali's dataset SemEval-Triplet-data that was open sourced, so that we can use it for research

Usage

1. 🍉 Download dataset from here SemEval-Triplet-data, ASTE-Data-V2-EMNLP2020 is used in my repository
2. 🥭 Download GloVe pre-trained word vectors,
3. 🍑 Convert glove_input_file in GloVe format to word2vec format and write it to `word2vec_output_file

from gensim.scripts.glove2word2vec import glove2word2vec

glove2word2vec("path/to/dir/glove_input_file", "path/to/dir/word2vec_output_file")

4. 🍓 train the span-aste model

python train.py --glove_word2vector vector_cache/w2v.txt \
          --dataset data/ASTE-Data-V2-EMNLP2020/15res/ \
          --output_path output/

5. 🍇 test the span-aste model

python test.py --model_path  \
          --glove_word2vector corpus/w2v.txt \
          --dataset data/ASTE-Data-V2-EMNLP2020/15res/\
          -model `path/to/model/model.pkl`