David Samuel
2022
Direct parsing to sentiment graphs
David Samuel
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Jeremy Barnes
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Robin Kurtz
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Stephan Oepen
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Lilja Øvrelid
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Erik Velldal
Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
This paper demonstrates how a graph-based semantic parser can be applied to the task of structured sentiment analysis, directly predicting sentiment graphs from text. We advance the state of the art on 4 out of 5 standard benchmark sets. We release the source code, models and predictions.
2021
ÚFAL at MultiLexNorm 2021: Improving Multilingual Lexical Normalization by Fine-tuning ByT5
David Samuel
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Milan Straka
Proceedings of the Seventh Workshop on Noisy User-generated Text (W-NUT 2021)
We present the winning entry to the Multilingual Lexical Normalization (MultiLexNorm) shared task at W-NUT 2021 (van der Goot et al., 2021a), which evaluates lexical-normalization systems on 12 social media datasets in 11 languages. We base our solution on a pre-trained byte-level language model, ByT5 (Xue et al., 2021a), which we further pre-train on synthetic data and then fine-tune on authentic normalization data. Our system achieves the best performance by a wide margin in intrinsic evaluation, and also the best performance in extrinsic evaluation through dependency parsing. The source code is released at https://github.com/ufal/multilexnorm2021 and the fine-tuned models at https://huggingface.co/ufal.
2020
ÚFAL at MRP 2020: Permutation-invariant Semantic Parsing in PERIN
David Samuel
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Milan Straka
Proceedings of the CoNLL 2020 Shared Task: Cross-Framework Meaning Representation Parsing
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Co-authors
- Milan Straka 2
- Jeremy Barnes 1
- Robin Kurtz 1
- Stephan Oepen 1
- Lilja Øvrelid 1
- show all...