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  # Tagger for literary character mentions (DROC corpus)
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- Thi is the character recognizer model that is being used in [LLpro](https://github.com/cophi-wue/LLpro). It detects character mentions in literary fiction: (a) proper nouns ("Alice", "Effi"), and (b) nominal phrases ("Gärtner", "Mutter", "Graf", "Idiot", "Schöne", ...). The model is trained on the [DROC dataset](https://gitlab2.informatik.uni-wuerzburg.de/kallimachos/DROC-Release), fine-tuning the domain-adapted [lkonle/fiction-gbert-large](https://huggingface.co/lkonle/fiction-gbert-large). ([Training code](https://github.com/cophi-wue/LLpro/blob/main/contrib/train_character_recognizer.py))
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  F1-Score: **91.85** (on a held-out data split; micro average on B-PER and I-PER labels)
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  # Tagger for literary character mentions (DROC corpus)
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+ This is the character recognizer model that is being used in [LLpro](https://github.com/cophi-wue/LLpro). It detects character mentions in literary fiction: (a) proper nouns ("Alice", "Effi"), and (b) nominal phrases ("Gärtner", "Mutter", "Graf", "Idiot", "Schöne", ...). The model is trained on the [DROC dataset](https://gitlab2.informatik.uni-wuerzburg.de/kallimachos/DROC-Release), fine-tuning the domain-adapted [lkonle/fiction-gbert-large](https://huggingface.co/lkonle/fiction-gbert-large). ([Training code](https://github.com/cophi-wue/LLpro/blob/main/contrib/train_character_recognizer.py))
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  F1-Score: **91.85** (on a held-out data split; micro average on B-PER and I-PER labels)
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