Triple

T5681207
Position Surface form Disambiguated ID Type / Status
Subject Darjeeling region of West Bengal, India E125202 entity
Predicate contains P35 FINISHED
Object Darjeeling town E162673 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: Darjeeling town | Statement: [Darjeeling region of West Bengal, India, contains, Darjeeling town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Darjeeling town
Context triple: [Darjeeling region of West Bengal, India, contains, Darjeeling town]
  • A. Darjeeling chosen
    Darjeeling is a famous hill station in the Indian Himalayas renowned for its tea plantations, scenic mountain views, and colonial-era charm.
  • B. Ranikhet
    Ranikhet is a hill station and cantonment town in the Kumaon region of Uttarakhand, India, known for its scenic Himalayan views and pleasant climate.
  • C. Nainital
    Nainital is a popular hill station and lake town in northern India, known for its scenic beauty 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. Mussoorie
    Mussoorie is a popular hill station in the Indian state of Uttarakhand, known for its scenic Himalayan views, colonial-era architecture, and role as a major educational and administrative training hub.
  • 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_69c0082a884c8190a79001bae658941f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c02397c01081909793bb53ad7cbbce completed March 22, 2026, 5:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69c05a35dd9c8190acd2ee8e94f309a6 completed March 22, 2026, 9:08 p.m.
Created at: March 22, 2026, 3:44 p.m.