The CRC Prominence in Language makes use of various sources of linguistic evidence and methods of analysis: data from neuro- and psycholinguistic experiments, data from elicitation tasks, production data from spontaneous speech and existing corpora, as well as results from tests assessing the acceptability of selected constructions. Project INF supports synergy between all CRC projects in the use of these methods. The project also takes the lead in ensuring data accountability and sustainability.

See list of publications

Publications

2024

• Ellison, T. Mark & Fahime Same. 2024. Experimental versus in-corpus variation in referring expression choice. In Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti & Nianwen Xue (eds.), Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), 6838–6848. Torino, Italia: ELRA & ICCL.
• Jasinskaja, Katja, Yuting Li, Fahime Same & David Uerlings. 2024. Reference and discourse structure annotation of elicited chat continuations in German. In Proceedings of the 18th Linguistic Annotation Workshop (LAW-XVIII), 176–187. St. Julians, Malta: Association for Computational Linguistics.

2023

• Chen, Guanyi, Fahime Same & Kees van Deemter. 2023. Neural referential form selection: Generalisability and interpretability. Computer Speech & Language 79. 101466.
• Repp, Magdalena, Petra B. Schumacher & Fahime Same. 2023. Multi-layered annotation of conversation-like narratives in German. In Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII), 61–72. Toronto: Association for Computational Linguistics.
• Same, Fahime, Guanyi Chen & Kees van Deemter. 2023. Models of reference production: How do they withstand the test of time? In Proceedings of the 16th International Natural Language Generation Conference, 93–105. Prague, Czechia: Association for Computational Linguistics.

2022

• Chen, Guanyi, Fahime Same & Kees van Deemter. 2022. Assessing Neural Referential Form Selectors on a Realistic Multilingual Dataset. In Proceedings of the 3rd Workshop on Evaluation and Comparison of NLP Systems, 103–114. Association for Computational Linguistics. pdf
• Ellison, T. Mark & Fahime Same. 2022. Constructing Distributions of Variation in Referring Expression Type from Corpora for Model Evaluation. In Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2989–2997. Marseille, France: European Language Resources Association. pdf
• Same, Fahime, Guanyi Chen & Kees van Deemter. 2022. Non-neural Models Matter: a Re-evaluation of Neural Referring Expression Generation Systems. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics, 5554–5567. Dublin, Ireland: Association for Computational Linguistics. pdf

2021

• Chen, Guanyi, Fahime Same & Kees van Deemter. 2021. What can Neural Referential Form Selectors Learn? In Proceedings of the 14th International Conference on Natural Language Generation, 154–166. Aberdeen, Scotland, UK: Association for Computational Linguistics. pdf

2020

• Same, Fahime & Kees van Deemter. 2020. A linguistic perspective on reference: choosing a feature set for generating referring expressions in context. Proceedings of the 28th international conference on computational linguistics (COLING) (Online-Konferenz), 4575–4586. Barcelona, Spain (Online): International Committee on Computational Linguistics.
• Same, Fahime & Kees van Deemter. 2020. Computational interpretations of recency for the choice of referring expressions in discourse. Proceedings of the first workshop on computational approaches to discourse (Online-Konferenz), 113–123. Online: Association for Computational Linguistics.

2018

• Leh, A., Köhler, J., Gref, M., & Himmelmann, N. P. 2018. Speech analytics in research based on qualitative interviews. Experiences from KA3. VIEW Journal of European Television History & Culture, 7(14), 138–149.
• Lobin, Henning, Roman Schneider & Andreas Witt (Eds.). 2018. Digitale Infrastrukturen für die germanistische Forschung. Berlin/Boston: de Gruyter. 
• Köhler, J., Leh, A., Himmelmann, N. P., & Rau, F. 2018. Audio Mining für die Geistes- und Kulturwissenschaften: Nutzungsszenarien und Herausforderungen. DHd 2018. Kritik Der Digitalen Vernunft. Conference abstracts. University of Cologne., 21-24. Cologne, Germany.

Event organization

• Organization of the workshop "Week of Writing", February 19-23, 2018, together with Sara Meuser (C05).
• Organization of the "R Stats User Group“ with biweekly meetings at the CRC 1252 (HoP, room 2.09).