Triple

T14026325
Position Surface form Disambiguated ID Type / Status
Subject Woodstock School E337465 entity
Predicate locatedIn P40 FINISHED
Object Mussoorie E67662 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: Mussoorie | Statement: [Woodstock School, locatedIn, Mussoorie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mussoorie
Context triple: [Woodstock School, locatedIn, Mussoorie]
  • A. Mussoorie chosen
    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.
  • B. Nainital
    Nainital is a popular hill station and lake town in northern India, known for its scenic beauty and colonial-era charm.
  • C. 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.
  • D. Rishikesh
    Rishikesh is a renowned town in the Indian state of Uttarakhand, famous as a center for yoga, meditation, and spiritual tourism along the banks of the Ganges River.
  • E. 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.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2fa6ca7481908976ce748a1957b1 completed April 14, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe249c57bc819089baed544fb8fead completed May 8, 2026, 5:59 p.m.
Created at: April 9, 2026, 10:20 p.m.