Triple

T247329
Position Surface form Disambiguated ID Type / Status
Subject Krishna River E5065 entity
Predicate basinState P8735 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: [Krishna River, basinState, Chhattisgarh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Chhattisgarh
Context triple: [Krishna River, basinState, 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. 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.
  • C. Rajasthan
    Rajasthan is a northwestern Indian state known for its vast Thar Desert, historic Rajput forts and palaces, and rich cultural heritage.
  • D. Gujarat
    Gujarat is a western coastal state of India known for its significant role in trade and industry, rich cultural heritage, and historic cities such as Ahmedabad.
  • E. Andhra Pradesh
    Andhra Pradesh is a state in southeastern India known for its long coastline along the Bay of Bengal, Telugu-speaking population, and major cities such as Visakhapatnam and Vijayawada.
  • 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_69a257c4bf688190a46ebbf411ab7473 completed Feb. 28, 2026, 2:49 a.m.
NER Named-entity recognition batch_69a260c592cc8190bc642fcd248a1f1b completed Feb. 28, 2026, 3:28 a.m.
NED1 Entity disambiguation (via context triple) batch_69a457fa35988190851216c84ad63232 completed March 1, 2026, 3:15 p.m.
Created at: Feb. 28, 2026, 2:54 a.m.