Triple

T7730474
Position Surface form Disambiguated ID Type / Status
Subject Koya E175235 entity
Predicate spokenIn P2266 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: [Koya, spokenIn, Chhattisgarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chhattisgarh
Context triple: [Koya, spokenIn, 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_69c6995e912c81909a49a2657103f786 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703358cf881909df8496d943d6de7 completed March 27, 2026, 10:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8d68a7e908190831b9f7f84ef19bd completed March 29, 2026, 7:36 a.m.
Created at: March 27, 2026, 4:06 p.m.