PETRA: Transforming Web Text for Petroleum-Engineering Domain Adaptation
Petroleum-engineering search exposes a supervision gap for strong general retrievers: relevant evidence exists in public web text, but domain relevance labels are scarce. To address this gap, we propose PETRA, a large-scale Petroleum Engineering Text for Retrieval Adaptation dataset and pipeline that converts noisy public web data into a curated domain corpus and synthetic supervision for dense retrieval and reranking. PETRA contains 1.36M curated chunks, approximately 2B token equivalents, $\approx$859k, embedding training rows from $\approx$224k anchors, and roughly 400k teacher-scored reranker candidate rows. Its construction combines high-recall energy-domain curation, an energy-domai...
| Authors | Kirill Dubovikov, Omar El Mansouri, Hachem Madmoun et al. |
|---|---|
| Primary category | cs.IR |
| Published | 23 June 2026 |
| Last updated at source | 23 June 2026 |
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