The Computational modelling of semantic change Tutorial will be hosted by EACL 2024 and will take place in Malta on the 21st of March 2024.
This tutorial provides an overview of current approaches, problems and challenges in the detection of lexical semantic change. At its core, computational modelling of semantic change consists of the following:
- Modelling word meaning, typically using unsupervised methods applied to diachronic corpora;
- modelling meaning change, based on the results of the above; and
- evaluation.
The tutorial will provide an introduction to lexical semantic change and an overview of the resources available (corpora, pre-trained diachronic models and data sets).
We will highlight issues related to the creation and use of diachronic corpora and different procedures for annotating data. We will then present the current state of the art in automatic detection of LSC, provide a hands-on section on available systems and tools, and open the floor for discussion on possible applications.
| Start-End | Title | Speaker(s) | Link(s) |
|---|
| 08.00- | Registration (Conference Center Registration Desk - Level 0) | | |
| 09.00-10.30 | Introduction to Semantic Change and Computational modeling | | |
| 09.00-09.20 | Introduction | Haim Dubossarsky | slides |
| 09.20-10.30 | Linguistic theory on semantic change | Stefano De Pascale | slides |
| 10.30-11.00 | Coffee Break | | |
| 11.00-12.30 | Evaluation: Tasks, benchmarks, and measurements of Lexical Semantic Change | | |
| 11.00-11.25 | Computational approaches to Semantics | Pierluigi Cassotti | slides |
| 11.25-11.40 | Human annotation of Lexical Semantic Change | Pierluigi Cassotti | slides |
| 11.40-11.45 | DURel Annotation Tool | Dominik Schlechtweg | DURel |
| 11.45-12.30 | Partisan and ad-hoc approaches | Haim Dubossarsky | slides |
| 12.30-14.00 | Lunch Break | | |
| 14.00-15.30 | Models for Lexical Semantic Change Detection | | |
| 14.00-15.00 | Computational models for Lexical Semantic Change | Francesco Periti | slides |
| 15.00-15.30 | Static Embedding and Temporal Alignment | Haim Dubossarsky | slides |
| 15.30-16.00 | Coffee Break | | |
| 16.00-16.30 | Advanced Contextualized Models | Pierluigi Cassotti | slides |
| 16.30-17.00 | Insights and Application | Haim Dubossarsky | slides |
| 17.00-17.30 | Hands-on | Pierluigi Cassotti | slides |
References:
- Nina Tahmasebi, Adam Jatowt, Lars Borin. Survey of Computational Approaches to Lexical Semantic Change Detection. Nina Tahmasebi, Lars Borin, Adam Jatowt, Yang Xu, Simon Hengchen (eds). Computational Approaches to Semantic Change. Berlin: Language Science Press.
- Geeraerts, D. (2020). Semantic Change. In The Wiley Blackwell Companion to Semantics (eds D. Gutzmann, L. Matthewson, C. Meier, H. Rullmann and T. Zimmermann).
- Stefano Montanelli and Francesco Periti, A Survey on Contextualised Semantic Shift Detection. (2023) arXiv:2304.01666.
- Francesco Periti and Nina TahmasebiA Systematic Comparison of Contextualized Word Embeddings for Lexical Semantic Change. (2024) arXiv:2402.12011.
- Simon Hengchen, Nina Tahmasebi, Dominik Schlechtweg, Haim Dubossarsky. Challenges for Computational Lexical Semantic Change. Nina Tahmasebi, Lars Borin, Adam Jatowt, Yang Xu, Simon Hengchen (eds). Computational Approaches to Semantic Change. Berlin: Language Science Press.
- Pierluigi Cassotti, Lucia Siciliani, Marco DeGemmis, Giovanni Semeraro, Pierpaolo Basile, XL-LEXEME: WiC Pretrained Model for Cross-Lingual LEXical sEMantic changE. (2023) In Proc. of ACL2023
- Francesco Periti, Sergio Picascia, Stefano Montanelli, Alfio Ferrara, and Nina Tahmasebi, Studying Word Meaning Evolution through Incremental Semantic Shift Detection: A Case Study of Italian Parliamentary Speeches. (2023) TechRxiv.
- Francesco Periti, Sergio Picascia, Stefano Montanelli, Alfio Ferrara, and Nina Tahmasebi, Studying Word Meaning Evolution through Incremental Semantic Shift Detection: A Case Study of Italian Parliamentary Speeches. (2023) TechRxiv.
- Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen, Haim Dubossarsky, and Barbara McGillivray. DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages. . In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 7079–7091, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.