Towards Universal Semantic Tagging
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Abstract (arXiv)
The paper proposes the task of universal semantic tagging---tagging word tokens with language-neutral, semantically informative tags. We argue that the task, with its independent nature, contributes to better semantic analysis for wide-coverage multilingual text. We present the initial version of the semantic tagset and show that (a) the tags provide semantically fine-grained information, and (b) they are suitable for cross-lingual semantic parsing. An application of the semantic tagging in the Parallel Meaning Bank supports both of these points as the tags contribute to formal lexical semantics and their cross-lingual projection. As a part of the application, we annotate a small corpus with the semantic tags and present new baseline result for universal semantic tagging.
Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 29 Sep 2017.
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Citing papers per year: 2021: 2; 2022: 1; 2023: 6; 2024: 2; 2025: 1.
12 papers.
- 2021What to Pre-Train on? Efficient Intermediate Task Selectioncited by 62
- 2023Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Trainingcited by 23
- 2021Does injecting linguistic structure into language models lead to better alignment with brain recordings?cited by 11
- 2024Multi-Document Financial Question Answering using LLMscited by 6
- 2022APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoningcited by 5
- 2024PMB5: Gaining More Insight into Neural Semantic Parsing with Challenging Benchmarkscited by 5
- 2023Semantic Operator Prediction and Applicationscited by 1
- 2023Semantic Tagging with LSTM-CRFcited by 0
- 2023Does Character-level Information Always Improve DRS-based Semantic Parsing?cited by 0
- 2023Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inferencecited by 0
- 2023Computational Semantics and Evaluation Benchmark for Interrogative Sentences via Combinatory Categorial Grammarcited by 0
- 2025FSLI: An Interpretable Formal Semantic System for One-Dimensional Ordering Inferencecited by 0
- 2025FSLI: An Interpretable Formal Semantic System for One-Dimensional Ordering Inference12 Feb 2025
- 2024Multi-Document Financial Question Answering using LLMs8 Nov 2024
- 2024PMB5: Gaining More Insight into Neural Semantic Parsing with Challenging Benchmarks12 Apr 2024
- 2023Computational Semantics and Evaluation Benchmark for Interrogative Sentences via Combinatory Categorial Grammar22 Dec 2023
- 2023Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training25 Oct 2023
- 2023Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference11 Jul 2023
- 2023Does Character-level Information Always Improve DRS-based Semantic Parsing?4 Jun 2023
- 2023Semantic Tagging with LSTM-CRF28 Jan 2023
- 2023Semantic Operator Prediction and Applications1 Jan 2023
- 2022APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning19 Dec 2022
- 2021What to Pre-Train on? Efficient Intermediate Task Selection16 Apr 2021
- 2021Does injecting linguistic structure into language models lead to better alignment with brain recordings?29 Jan 2021