Carolina Flinz


2024

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Dates and places as points of attachment for memorial contents in the ISW corpus: 1938 as a turning point
Carolina Flinz | Simona Leonardi
Proceedings of the First Workshop on Holocaust Testimonies as Language Resources (HTRes) @ LREC-COLING 2024

Aim of the paper is the identification and subsequent analysis of crisis years in the narrative biographical interviews with German speaking Jews from the corpus ISW (Emigrantendeutsch in Israel: Wiener in Jerusalem/ Migrant German in Israel: Viennese in Jerusalem); also the possible “chronological landmarks” within a year will be tackled, investigating how a certain year – 1938 – represents in the life story of the narrators a turning point, as it clusters most traumatic events linked to the Shoah. The transcripts were analysed using the tool Sketch Engine. An alternation of corpus-driven and corpus-based steps characterizes this study, which uses a quantitative-qualitative approach (see Lemnitzer and Zinsmeister, 2015) and integrates also approaches from narrative analysis. The research questions that guide our investigation are as follows: Are there any special dates that recur as chronological landmarks of crisis situations (Leonardi 2023a)? Which are they? Do they recur in connection with special places? which ones?

2020

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Fine-grained Named Entity Annotations for German Biographic Interviews
Josef Ruppenhofer | Ines Rehbein | Carolina Flinz
Proceedings of the Twelfth Language Resources and Evaluation Conference

We present a fine-grained NER annotations with 30 labels and apply it to German data. Building on the OntoNotes 5.0 NER inventory, our scheme is adapted for a corpus of transcripts of biographic interviews by adding categories for AGE and LAN(guage) and also features extended numeric and temporal categories. Applying the scheme to the spoken data as well as a collection of teaser tweets from newspaper sites, we can confirm its generality for both domains, also achieving good inter-annotator agreement. We also show empirically how our inventory relates to the well-established 4-category NER inventory by re-annotating a subset of the GermEval 2014 NER coarse-grained dataset with our fine label inventory. Finally, we use a BERT-based system to establish some baseline models for NER tagging on our two new datasets. Global results in in-domain testing are quite high on the two datasets, near what was achieved for the coarse inventory on the CoNLLL2003 data. Cross-domain testing produces much lower results due to the severe domain differences.