# Towards Universal Semantic Tagging

arXiv: https://arxiv.org/abs/1709.10381 · HTML: https://mlsanity.com/paper/1709.10381/

## Key facts

- Cited by 12 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 29 Sep 2017.

## Built on by (most cited first, 12 of 12)

- [What to Pre-Train on? Efficient Intermediate Task Selection](https://mlsanity.com/paper/2104.08247/) (2021)
- [Subspace Chronicles: How Linguistic Information Emerges, Shifts and Interacts during Language Model Training](https://mlsanity.com/paper/2310.16484/) (2023)
- [Does injecting linguistic structure into language models lead to better alignment with brain recordings?](https://mlsanity.com/paper/2101.12608/) (2021)
- [Multi-Document Financial Question Answering using LLMs](https://mlsanity.com/paper/2411.07264/) (2024)
- [APOLLO: A Simple Approach for Adaptive Pretraining of Language Models for Logical Reasoning](https://mlsanity.com/paper/2212.09282/) (2022)
- [PMB5: Gaining More Insight into Neural Semantic Parsing with Challenging Benchmarks](https://mlsanity.com/paper/2404.08354/) (2024)
- [Semantic Operator Prediction and Applications](https://mlsanity.com/paper/2301.00399/) (2023)
- [Semantic Tagging with LSTM-CRF](https://mlsanity.com/paper/2301.12206/) (2023)
- [Does Character-level Information Always Improve DRS-based Semantic Parsing?](https://mlsanity.com/paper/2306.02302/) (2023)
- [Synthetic Dataset for Evaluating Complex Compositional Knowledge for Natural Language Inference](https://mlsanity.com/paper/2307.05034/) (2023)
- [Computational Semantics and Evaluation Benchmark for Interrogative Sentences via Combinatory Categorial Grammar](https://mlsanity.com/paper/2312.14737/) (2023)
- [FSLI: An Interpretable Formal Semantic System for One-Dimensional Ordering Inference](https://mlsanity.com/paper/2502.08415/) (2025)

## 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.