matthewfranglen/aste-v2
Dataset Description Task Summary Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the sentiment. This task is firstly proposed by (Peng et al., 2020) in the paper Knowing What, How and Why: A Near Complete Solution for Aspect-based Sentiment Analysis (In AAAI 2020). For Example, given the sentence: The screen is very large and crystal clear… See the full description on the dataset page: https://huggingface.co/datasets/matthewfranglen/aste-v2.
| Author / organization | matthewfranglen |
|---|---|
| Downloads | 255 (as reported by Hugging Face) |
| Likes | 0 |
| Created | 7 October 2023 |
| Last updated at source | 9 October 2023 |
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255 now (+1 since 2026-10-16). Counts as reported by the source, snapshotted daily by Silytics.
Recent changes
- 17 Oct 2026 Description: Dataset Description Task Summary Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the sentiment. This task is first → Dataset Description Task Summary Aspect Sentiment Triplet Extraction (ASTE) is the task of extracting the triplets of target entities, their associated sentiment, and opinion spans explaining the reason for the sentiment. This task is first
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