Triple

T16769644
Position Surface form Disambiguated ID Type / Status
Subject Kisan language E407558 entity
Predicate region P40 FINISHED
Object Chhattisgarh E30868 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: Chhattisgarh | Statement: [Kisan language, region, Chhattisgarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chhattisgarh
Context triple: [Kisan language, region, Chhattisgarh]
  • A. Chhattisgarh chosen
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • B. Jharkhand
    Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
  • C. Madhya Pradesh
    Madhya Pradesh is a large central Indian state known for its historical cities, diverse tribal cultures, and significant forested and wildlife areas including several major national parks.
  • D. Chhattisgarhi
    Chhattisgarhi is an Indo-Aryan language spoken primarily in the Indian state of Chhattisgarh and surrounding regions.
  • E. Rajasthan
    Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
  • 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_69d8839174188190909f190097207065 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b0356a9c8190b316cd00223e7537 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c798389c8190aa9865d9aa746da5 completed May 10, 2026, 5:59 p.m.
Created at: April 10, 2026, 5:21 a.m.