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MIRACL-id with five -nya preprocessing strategies
This dataset is a derivative work of MIRACL (Zhang et al., 2023)
restricted to the Indonesian (id) subset, preprocessed five different ways
to study how Indonesian -nya clitic handling affects retrieval quality.
Licensed under Apache-2.0, matching MIRACL.
Preprocessing strategies
keep
Baseline pass-through. Text is preserved exactly as MIRACL ships it.
naive_strip
Every word ending in -nya has the suffix stripped unconditionally. Includes false positives like punya, tanya, hanya, Kenya — this strategy exists as a deliberately bad baseline.
sastrawi_clitic
PySastrawi's RemoveInflectionalPossessivePronoun visitor, guarded by the bundled 29,931-root Indonesian dictionary so that punya/tanya/hanya/Kenya are recognised as roots and preserved.
sentinel
Like sastrawi_clitic, but the stripped suffix is replaced with the literal token <NYA>. Lets a retriever learn that something clitic-shaped was here without committing to a specific reading.
rule_resolved
Rule-based resolver: when a -nya form is preceded within ~2 sentences by a capitalised antecedent that is itself not a -nya form, the suffix is replaced by that antecedent. Falls through to keep when no antecedent is found. This is an in-house heuristic, NOT the IndoCoref system (Artari et al., 2021); see the paper's Limitations section.
Layout
README.md (this file)
root_dict.txt Sastrawi root dictionary (29,931 entries, Path A)
sensitivity_annotations.csv Per-query H5 sensitivity (alpha=1*total + beta=2*anaphoric + gamma=3*entity_ref) + tertile
qrels/qrels_dev.txt TREC 4-column qrels extracted from MIRACL dev positives
keep/ queries_dev.jsonl (960 rows), corpus_train.jsonl (1446315 rows)
naive_strip/ queries_dev.jsonl (960 rows), corpus_train.jsonl (1446315 rows)
sastrawi_clitic/ queries_dev.jsonl (960 rows), corpus_train.jsonl (1446315 rows)
sentinel/ queries_dev.jsonl (960 rows), corpus_train.jsonl (1446315 rows)
rule_resolved/ queries_dev.jsonl (960 rows), corpus_train.jsonl (1446315 rows)
All JSONL files have two fields: id (str) and contents (str).
Loadable with datasets.load_dataset("maskrio/nya-ir-miracl-id-preprocessed", data_files=...)
or with the Pyserini / sentence-transformers ingestion paths.
Citation
If you use this dataset, please cite both MIRACL and this work:
@article{zhang2023miracl,
title={MIRACL: A Multilingual Retrieval Dataset Covering 18 Diverse Languages},
author={Zhang, Xinyu and others},
journal={Transactions of the ACL},
year={2023}
}
Reproducibility
Everything here is reproducible from the code repo via
scripts/run_preprocessing_sweep.py followed by
scripts/upload_to_hf.py. The Sastrawi dictionary (root_dict.txt) is
shipped alongside the data so that the dictionary-guarded strategies
(sastrawi_clitic, rule_resolved) can be reproduced bit-for-bit even
if PySastrawi ships a different kata-dasar.txt in a future release.
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