redewiedergabe-freeindirect

REDEWIEDERGABE Tagger: free indirect STWR

This model is part of an ensemble of binary taggers that recognize German speech, thought and writing representation, that is being used in LLpro. They can be used to automatically detect and annotate the following 4 types of speech, thought and writing representation in German texts:

The ensemble is trained on the REDEWIEDERGABE corpus (Annotation guidelines), fine-tuning each tagger on the domain-adapted lkonle/fiction-gbert-large. (Training Code)

F1-Scores:

---

Demo Usage:

from flair.data import Sentence
from flair.models import SequenceTagger


sentence = Sentence('Sie sprachen über das Mittagessen. Sie fragte, wo das Essen sei. Woher sollte er das wissen? Dann sagte er: "Ich habe Hunger."')

rwtypes = ['direct', 'indirect', 'freeindirect', 'reported']
for rwtype in rwtypes:
    model = SequenceTagger.load(f'aehrm/redewiedergabe-{rwtype}')
    model.predict(sentence)
    print(rwtype, [ x.data_point.text for x in sentence.get_labels() ])
# >>> direct ['"', 'Ich', 'habe', 'Hunger', '.', '"']
# >>> indirect ['wo', 'das', 'Essen', 'sei', '.']
# >>> freeindirect ['Woher', 'sollte', 'er', 'das', 'wissen', '?']
# >>> reported ['Sie', 'sprachen', 'über', 'das', 'Mittagessen', '.', 'Woher', 'sollte', 'er', 'das', 'wissen', '?']

Cite:

Please cite the following paper when using this model.

@inproceedings{ehrmanntraut-et-al-llpro-2023,
	address = {Ingolstadt, Germany},
	title = {{LLpro}: A Literary Language Processing Pipeline for {German} Narrative Text},
	booktitle = {Proceedings of the 10th Conference on Natural Language Processing ({KONVENS} 2022)},
	publisher = {{KONVENS} 2023 Organizers},
	author = {Ehrmanntraut, Anton and Konle, Leonard and Jannidis, Fotis},
	year = {2023},
}