Indonesian BERT Named Entity Recognition (NER) Pipeline
This repository contains a fine-tuned IndoBERT model for Indonesian Named Entity Recognition, wrapped in a HuggingFace-compatible pipeline for easy usage.
π Quick Start
from transformers import pipeline
ner = pipeline(
"ner",
model="fahmisyaifudin/indobert_ner_p1",
tokenizer="fahmisyaifudin/indobert_ner_p1",
aggregation_strategy="simple"
)
text = "Hadiri KTT G20, Momen Gibran Bersama Erdogan hingga PM Jepang"
entities = ner(text)
print(entities)
# Output: [{'entity_group': 'EVENT', 'score': np.float32(0.9938912), 'word': 'ktt g20', 'start': 7, 'end': 14}, {'entity_group': 'PERSON', 'score': np.float32(0.80416846), 'word': 'gibran', 'start': 22, 'end': 28}, {'entity_group': 'PERSON', 'score': np.float32(0.99820226), 'word': 'erdogan', 'start': 37, 'end': 44}, {'entity_group': 'REPRESENTATIVE_PERSON', 'score': np.float32(0.9186572), 'word': 'pm jepang', 'start': 52, 'end': 61}]
π― Supported Entity Types
- PERSON β Names of individual humans
- REPRESENTATIVE_PERSON β Government/public roles
- POLITICAL_ORGANIZATION β Constitutional political institutions
- ORGANIZATION β Companies, universities, BUMN , NGOs
- LAW β UU, UUD, Kepres
- EVENT β National events, gov programs
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