rajdeep345/PASTE
Codes and Datasets for our EMNLP 2021 (main conference) Long Paper titled "PASTE: A Tagging-Free Decoding Framework Using Pointer Networks for Aspect Sentiment Triplet Extraction"
This project offers a sophisticated method for analyzing text to extract specific opinions. It takes raw text, such as customer reviews or social media posts, and identifies the exact aspects being discussed, the sentiment towards them, and the holder of that opinion. This is ideal for data scientists or NLP researchers who need to perform detailed sentiment analysis beyond simple positive/negative labels.
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Use this if you need to precisely identify specific aspects, their associated sentiments, and the opinion holder from unstructured text data.
Not ideal if you're looking for a user-friendly, out-of-the-box sentiment analysis tool without needing to dive into model training and configuration.
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Language
Python
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Last pushed
May 20, 2021
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