The TTLab (Text Technology Lab), headed by Prof. Alexander Mehler, is part of the Department of Computer Science and Mathematics (Fachbereich Informatik und Mathematik) at the Goethe Universität in Frankfurt. It investigates formal, algorithmic models to deepen our understanding of information processing in the humanities. We examine diachronic, time-dependent as well as synchronic aspects of processing linguistic and non-linguistic, multimodal signs. The Lab works across several disciplines to bridge between computer science on the one hand and corpus-based research in the humanities on the other. To this end, we develop information models and algorithms for the analysis of texts, images, and other objects relevant to research in the humanities.
News
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New publication accepted in ACL Findings 2025
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Our paper, “Filling the Temporal Void: Recovering Missing Publication Years in the Project Gutenberg Corpus Using LLMs“, has been accepted to the Findings of the 63rd Annual Meeting of the Association for Computational Linguistics (ACL 2025).
2025. Filling the Temporal Void: Recovering Missing Publication Years in the Project Gutenberg Corpus Using LLMs. Findings of the 63rd Annual Meeting of the Association for Computational Linguistics. accepted.BibTeX@inproceedings{Momen:Schaaf:Mehler:2025, title = {Filling the Temporal Void: Recovering Missing Publication Years in the Project Gutenberg Corpus Using {LLM}s}, author = {Momen, Omar and Schaaf, Manuel and Mehler, Alexander}, booktitle = {Findings of the 63rd Annual Meeting of the Association for Computational Linguistics}, year = {2025}, note = {accepted} } -
Best Demo Award at NAACL 2025
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We are delighted that our paper “Towards Unified, Dynamic, and Annotation-based Visualizations and Exploration of Annotated Big Data Corpora with the Help of Unified Corpus Explorer” has been awarded the Best Demo Paper at this year’s annual conference of the Nations of the Americas Chapter of the Association for Computational Linguistics (NAACL 2025).
2025. Towards Unified, Dynamic and Annotation-based Visualisations and Exploration of Annotated Big Data Corpora with the Help of Unified Corpus Explorer. Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations), 522–534. Best Demo Award.BibTeX@inproceedings{Boenisch:et:al:2025, title = {Towards Unified, Dynamic and Annotation-based Visualisations and Exploration of Annotated Big Data Corpora with the Help of Unified Corpus Explorer}, author = {B{\"o}nisch, Kevin and Abrami, Giuseppe and Mehler, Alexander}, editor = {Dziri, Nouha and Ren, Sean (Xiang) and Diao, Shizhe}, booktitle = {Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (System Demonstrations)}, year = {2025}, address = {Albuquerque, New Mexico}, publisher = {Association for Computational Linguistics}, url = {https://aclanthology.org/2025.naacl-demo.42/}, pages = {522--534}, isbn = {979-8-89176-191-9}, abstract = {The annotation and exploration of large text corpora, both automatic and manual, presents significant challenges across multiple disciplines, including linguistics, digital humanities, biology, and legal science. These challenges are exacerbated by the heterogeneity of processing methods, which complicates corpus visualization, interaction, and integration. To address these issues, we introduce the Unified Corpus Explorer (UCE), a standardized, dockerized, open-source and dynamic Natural Language Processing (NLP) application designed for flexible and scalable corpus navigation. Herein, UCE utilizes the UIMA format for NLP annotations as a standardized input, constructing interfaces and features around those annotations while dynamically adapting to the corpora and their extracted annotations. We evaluate UCE based on a user study and demonstrate its versatility as a corpus explorer based on generative AI.}, note = {Best Demo Award}, pdf = {https://aclanthology.org/2025.naacl-demo.42.pdf} } -
New publication in the proceedings of “Sinn und Bedeutung” coming soon
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Referential Transparency Theory (RTT) now also covers mass nouns!
The authors argue that much of the work on pluralities and mass nouns in in so-called modern semantic theories primarily seeks to mitigate the effects of mereotopological domains. They therefore abandon such domains in favor of the RTT system, extended by a novel quantitative semantic type Stuff. Crucial notions such as cumulative and divisive reference emerge naturally from this independently motivated setup. Rather idiosyncratic internal parthood relations of nominal expressions are appropriately captured in lexical entries.
2025. Postmodern Quantification with Stuff. Proceedings of Sinn und Bedeutung, 29. Forthcoming.BibTeX@inproceedings{Luecking:Ginzburg:2025-mass-nouns, title = {Postmodern Quantification with Stuff}, author = {Lücking, Andy and Ginzburg, Jonathan}, booktitle = {Proceedings of \textit{Sinn und Bedeutung}}, volume = {29}, series = {SuB'29}, year = {2025}, pubstate = {forthcoming}, note = {Forthcoming} }
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