Papers › Seq2Path: Generating Sentiment Tuples as Paths of a Tree
Seq2Path: Generating Sentiment Tuples as Paths of a Tree
Yue Mao, Yi Shen, Jingchao Yang, Xiaoying Zhu, Longjun Cai
Aspect-based sentiment analysis (ABSA) tasks aim to extract sentiment tuples from a sentence. Recent generative methods such as Seq2Seq models have achieved good performance by formulating the output as a sequence of sentiment tuples. However, the orders between the sentiment tuples do not naturally exist and the generation of the current tuple should not condition on the previous ones. In this paper, we propose Seq2Path to generate sentiment tuples as paths of a tree. A tree can represent “1-to-n” relations (e.g., an aspect term may correspond to multiple opinion terms) and the paths of a tree are independent and do not have orders. For training, we treat each path as an independent target, and we calculate the average loss of the ordinary Seq2Seq model over paths. For inference, we apply beam search with constrained decoding. By introducing an additional discriminative token and applying a data augmentation technique, valid paths can be automatically selected. We conduct experiments on five tasks including AOPE, ASTE, TASD, UABSA, ACOS. We evaluate our method on four common benchmark datasets including Laptop14, Rest14, Rest15, Rest16. Our proposed method achieves state-of-the-art results in almost all cases.
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Aspect-Based Sentiment Analysis (ABSA) | ASTE | Seq2Path | F1 (L14) | 64.82 | #3 of 13 | Archive leaderboard | report |
| Aspect-Based Sentiment Analysis (ABSA) | ASTE | Seq2Path | F1 (R15) | 65.88 | #3 of 13 | Archive leaderboard | report |
| Aspect-Based Sentiment Analysis (ABSA) | ASTE | Seq2Path | F1 (R16) | 72.87 | #3 of 13 | Archive leaderboard | report |
| Aspect-Based Sentiment Analysis (ABSA) | ASTE | Seq2Path | F1(R14) | 75.52 | #3 of 13 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
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