Triple

T13901027
Position Surface form Disambiguated ID Type / Status
Subject Nilgiris district E334221 entity
Predicate contains P35 FINISHED
Object Coonoor E183720 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: Coonoor | Statement: [Nilgiris district, contains, Coonoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Coonoor
Context triple: [Nilgiris district, contains, Coonoor]
  • A. Coonoor chosen
    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.
  • B. 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.
  • C. 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.
  • D. 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.
  • E. Coorg
    Coorg, also known as Kodagu, is a scenic hill district in Karnataka, India, famed for its coffee plantations, lush forests, and mist-covered landscapes.
  • 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_69d81c5eaa9c819083b1ff8689179565 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de25d9c7a48190ad8fb0ca676f4f7b completed April 14, 2026, 11:32 a.m.
NED1 Entity disambiguation (via context triple) batch_69fba1c0b6848190b67051e0ccbdb707 completed May 6, 2026, 8:17 p.m.
Created at: April 9, 2026, 10:15 p.m.