Triple

T19363254
Position Surface form Disambiguated ID Type / Status
Subject Shikohabad E484332 entity
Predicate partOf P40 FINISHED
Object Agra division NE NERFINISHED

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: Agra division | Statement: [Shikohabad, partOf, Agra division]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Agra division
Context triple: [Shikohabad, partOf, Agra division]
  • A. Agra division chosen
    Agra division is an administrative division in the Indian state of Uttar Pradesh that includes the city of Agra and surrounding districts.
  • B. Agra district
    Agra district is an administrative district in the Indian state of Uttar Pradesh, best known for encompassing the city of Agra, home to the Taj Mahal.
  • C. Agra Province
    Agra Province was a major administrative region of British India centered on the city of Agra, forming part of the North-Western Provinces under colonial rule.
  • D. Agra metropolitan area
    The Agra metropolitan area is the urban agglomeration centered on the historic city of Agra in Uttar Pradesh, India, encompassing its surrounding suburbs and satellite localities.
  • E. Aligarh district
    Aligarh district is an administrative region in the Indian state of Uttar Pradesh, known for the city of Aligarh and its prominent educational and lock industries.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619a897008190a2c62a50ca60de2d completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:34 p.m.