Triple

T13020677
Position Surface form Disambiguated ID Type / Status
Subject Virajpet E326161 entity
Predicate region P40 FINISHED
Object Coorg E325184 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: Coorg | Statement: [Virajpet, region, Coorg]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coorg
Context triple: [Virajpet, region, Coorg]
  • A. Coorg chosen
    Coorg, also known as Kodagu, is a scenic hill district in Karnataka, India, famed for its coffee plantations, lush forests, and mist-covered landscapes.
  • B. Munnar
    Munnar is a popular hill station in the Western Ghats of southern India, renowned for its sprawling tea plantations, cool climate, and scenic mountain landscapes.
  • C. Coonoor
    Coonoor is a scenic hill station in the Nilgiri Hills of Tamil Nadu, India, known for its tea plantations, cool climate, and colonial-era charm.
  • D. Ooty
    Ooty is a popular hill station in the Nilgiri Hills of southern India, known for its cool climate, tea plantations, and scenic mountain landscapes.
  • E. Yercaud
    Yercaud is a scenic hill station in Tamil Nadu’s Eastern Ghats, known for its cool climate, coffee plantations, and views over the surrounding plains.
  • 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_69d8076cc45c81908123123f43e69266 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ecf21bc819082fb512bc479b4be completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbc98e10819091d71198bca1ac12 completed May 3, 2026, 4:15 a.m.
Created at: April 9, 2026, 8:51 p.m.