Triple

T13298378
Position Surface form Disambiguated ID Type / Status
Subject Kausani E316743 entity
Predicate locatedNear P294 FINISHED
Object Bageshwar E312908 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: Bageshwar | Statement: [Kausani, locatedNear, Bageshwar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bageshwar
Context triple: [Kausani, locatedNear, Bageshwar]
  • A. Bageshwar chosen
    Bageshwar is a town and district headquarters in the Kumaon region of Uttarakhand, India, known for its religious significance and scenic Himalayan surroundings.
  • B. Mukteshwar
    Mukteshwar is a scenic hill town in Uttarakhand, India, known for its panoramic Himalayan views, fruit orchards, and tranquil forests.
  • C. Badrinath
    Badrinath is a prominent Hindu temple town in the Indian Himalayas, revered as one of the Char Dham and an important pilgrimage destination dedicated to Lord Vishnu.
  • D. Sangameshwar
    Sangameshwar is a town in Maharashtra, India, historically notable as the site where Maratha ruler Sambhaji was captured by Mughal forces.
  • E. Rudrapur
    Rudrapur is a town in the Indian state of Uttar Pradesh, known as a local commercial and agricultural center in the region.
  • 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_69d806b40ab4819094adf6c374f4811a completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d990a2f2708190a8f2aa7e7c0b92d2 completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7266a316c81908361acc75581f211 completed May 3, 2026, 10:41 a.m.
Created at: April 9, 2026, 9:28 p.m.