Triple

T14522757
Position Surface form Disambiguated ID Type / Status
Subject F. J. Shore E340692 entity
Predicate associatedWith P37 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: [F. J. Shore, associatedWith, Mussoorie]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mussoorie
Context triple: [F. J. Shore, associatedWith, 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_69d822dac79c8190a84a073f3cbaced5 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69dea04f16f88190ba357b0f8021b46b completed April 14, 2026, 8:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fea59f26188190b81af88940a9c95b completed May 9, 2026, 3:10 a.m.
Created at: April 10, 2026, 1:22 a.m.