PedroDKE/multilingual-ner-abb-improved

Multilingual (English, Dutch, German) NER model for legal/administrative decision documents.

This improved version adds native German training data (municipal decisions from Freiburg and Bamberg) on top of the original Dutch (Ghent) and English (translated) data, improving detection quality on German text and on text translated from German.

  • Base model: xlm-roberta-base
  • Languages: English (en), Dutch (nl), German (de)
  • Labels (BIO): DATE, LOCATION, LEGAL_GROUND, ADMINISTRATIVE_BODY, MANDATARY

Quickstart

from transformers import pipeline

ner = pipeline("token-classification", model="PedroDKE/multilingual-ner-abb-improved", aggregation_strategy="simple")

# German
print(ner("Der Stadtrat der Stadt Bamberg hat am 12. Mรคrz 2024 beschlossen."))

# Dutch
print(ner("De gemeenteraad van Gent heeft op 12 maart 2024 besloten."))

# English
print(ner("The city council of London decided on March 12, 2024."))

Evaluation

strict (seqeval, entity-level) micro on held-out validation set.

Language Samples Precision Recall F1
ALL 920 0.766 0.823 0.794
EN 57 0.675 0.705 0.690
NL 69 0.751 0.783 0.767
DE 794 0.785 0.855 0.818

Per-label (strict) โ€” ALL

Label Precision Recall F1 Support
ADMINISTRATIVE_BODY 0.76 0.86 0.81 459
DATE 0.84 0.88 0.86 773
LEGAL_GROUND 0.82 0.85 0.84 362
LOCATION 0.61 0.66 0.63 678
MANDATARY 0.82 0.88 0.85 580

Per-label (strict) โ€” EN

Label Precision Recall F1 Support
ADMINISTRATIVE_BODY 0.64 0.72 0.68 64
DATE 0.67 0.66 0.67 59
LEGAL_GROUND 0.63 0.75 0.69 32
LOCATION 0.38 0.62 0.47 32
MANDATARY 0.85 0.72 0.78 138

Per-label (strict) โ€” NL

Label Precision Recall F1 Support
ADMINISTRATIVE_BODY 0.60 0.67 0.63 58
DATE 0.77 0.91 0.84 104
LEGAL_GROUND 0.67 0.74 0.71 47
LOCATION 0.70 0.61 0.65 174
MANDATARY 0.85 0.91 0.88 188

Per-label (strict) โ€” DE

Label Precision Recall F1 Support
ADMINISTRATIVE_BODY 0.81 0.92 0.86 337
DATE 0.87 0.90 0.89 610
LEGAL_GROUND 0.88 0.88 0.88 283
LOCATION 0.61 0.68 0.64 472
MANDATARY 0.80 0.95 0.87 254
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