Triple

T13712409
Position Surface form Disambiguated ID Type / Status
Subject Babatpur E328805 entity
Predicate roadConnection P385 FINISHED
Object Ghazipur E331718 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: Ghazipur | Statement: [Babatpur, roadConnection, Ghazipur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghazipur
Context triple: [Babatpur, roadConnection, Ghazipur]
  • A. Ghazipur chosen
    Ghazipur is a city in the Indian state of Uttar Pradesh, known for its historical significance and as a regional hub in eastern Uttar Pradesh.
  • B. Farrukhabad
    Farrukhabad is a city and parliamentary constituency in the Indian state of Uttar Pradesh, known historically for its trade and cultural significance.
  • C. Shahjahanpur
    Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
  • D. Unnao
    Unnao is a city in northern India known for its historical significance and its location between the major urban centers of Lucknow and Kanpur in Uttar Pradesh.
  • E. Chandauli
    Chandauli is a town and administrative district headquarters in the eastern Indian state of Uttar Pradesh, known for its agricultural economy and proximity to Varanasi.
  • 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_69d80770b9bc81909f70c8c317d53cff completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dd4395e8c0819098719c8cd344aa33 completed April 13, 2026, 7:27 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1b661e4819087bac0cd84489baa completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 9:54 p.m.