aehrm / 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},
}