mlsanityData to 7 Oct 2026

Multilingual Normalization of Temporal Expressions with Masked Language Models

arXiv 2205.10399 ↗First posted 20 May 2022cs.CL cs.LGcited by 7

Not on the map. Why?

Abstract (arXiv)

The detection and normalization of temporal expressions is an important task and preprocessing step for many applications. However, prior work on normalization is rule-based, which severely limits the applicability in real-world multilingual settings, due to the costly creation of new rules. We propose a novel neural method for normalizing temporal expressions based on masked language modeling. Our multilingual method outperforms prior rule-based systems in many languages, and in particular, for low-resource languages with performance improvements of up to 33 F1 on average compared to the state of the art.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Builds on 11 of its 48 references that are in the map. First posted on arXiv 20 May 2022.

Builds on

11 of 48 references.

References · 11

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  2. 2020Language Models are Few-Shot Learnerscited by 32,199
  3. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  4. 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
  5. 2018Massively Multilingual Sentence Embeddings for Zero-Shot Cross-Lingual Transfer and Beyondcited by 434
  6. 2020Autoregressive Entity Retrievalcited by 333
  7. 2021PTR: Prompt Tuning with Rules for Text Classificationcited by 238
  8. 2020A Survey on Recent Approaches for Natural Language Processing in Low-Resource Scenarioscited by 170
  9. 2021Template-free Prompt Tuning for Few-shot NERcited by 73
  10. 2021Paradigm Shift in Natural Language Processingcited by 39
  11. 2020Adversarial Alignment of Multilingual Models for Extracting Temporal Expressions from Textcited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 2; 2026: 3.

7 papers.

  1. 2024AnnoCTR: A Dataset for Detecting and Linking Entities, Tactics, and Techniques in Cyber Threat Reportscited by 2
  2. 2024Discourse-Aware In-Context Learning for Temporal Expression Normalizationcited by 2
  3. 2025Transformer-Based Temporal Information Extraction and Application: A Reviewcited by 1
  4. 2025A Semantic Parsing Framework for End-to-End Time Normalizationcited by 1
  5. 2026Reproducing Omitted Temporal Expressions in Japanese News for Retrieval-Augmented Applicationscited by 0
  6. 2026Q-TIE: A Lightweight and Generalizable Re-ranking Framework for Temporal Information Retrievalcited by 0
  7. 2026TEMPS: Temporal Sentence Embeddings for Temporal Information Retrievalcited by 0