Der SFB Prominenz in Sprache verwendet unterschiedliche Evidenzquellen und Analysemethoden, z.B. Daten aus neuro- und psycholinguistischen Experimenten, elizitierte Daten, Produktionsdaten (einschließlich Spontansprache) und Akzeptabilitätstests. Projekt INF stellt sicher, dass Synergiepotentiale bei der Datenerhebung, -aufbereitung und -archivierung genutzt werden und dass die Daten überprüfbar und nachhaltig nutzbar bleiben.

Zu den Projektpublikationen

Publikationen

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. Konferenzabstracts. Universität zu Köln., 21-24. Köln.

Organisation von Veranstaltungen

• Organisation des Workshop "Week of Writing", 19.-23 Februar, 2018, gemeinsam mit Sara Meuser (C05).
• Organisation der „R Stats User Group“ mit regelmäßigen zweiwöchentlichen Treffen am SFB 1252.