Triple

T1456660
Position Surface form Disambiguated ID Type / Status
Subject Eastern India E31415 entity
Predicate hasSubregion P285 FINISHED
Object Odisha region E76751 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Odisha region | Statement: [Eastern India, hasSubregion, Odisha region]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odisha region
Context triple: [Eastern India, hasSubregion, Odisha region]
  • A. Odisha (parts)
    Odisha (parts) refers to those areas of the modern Indian state of Odisha that were historically administered under the British-era Madras Presidency.
  • B. Orissa chosen
    Orissa is a historical region and modern Indian state on the eastern coast of India, known for its rich cultural heritage, ancient temples, and significant role in the subcontinent’s political and economic history.
  • C. West Bengal
    West Bengal is an eastern Indian state known for its cultural heritage, literature, and the metropolis of Kolkata (formerly Calcutta).
  • D. Jharkhand
    Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
  • E. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69a49917dfc081909acdbdf5d684f1ef completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c598b30c8190b87207adf608b89a completed March 1, 2026, 11:02 p.m.
NED1 Entity disambiguation (via context triple) batch_69b20309280c8190ad9a73397e42267c completed March 12, 2026, 12:04 a.m.
Created at: March 1, 2026, 8 p.m.