Triple

T9174289
Position Surface form Disambiguated ID Type / Status
Subject Shahjahanpur district E220157 entity
Predicate hasAdministrativeHeadquarters P1474 FINISHED
Object Shahjahanpur E280629 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: Shahjahanpur | Statement: [Shahjahanpur district, hasAdministrativeHeadquarters, Shahjahanpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shahjahanpur
Context triple: [Shahjahanpur district, hasAdministrativeHeadquarters, Shahjahanpur]
  • A. Shahjahanpur chosen
    Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
  • B. Bulandshahr
    Bulandshahr is a city in the Indian state of Uttar Pradesh known for its historical significance and proximity to Delhi within the broader metropolitan region.
  • C. Jaunpur
    Jaunpur is a historic city in the Indian state of Uttar Pradesh, known for its medieval architecture and cultural heritage.
  • D. Moradabad
    Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
  • E. Farrukhabad
    Farrukhabad is a city and parliamentary constituency in the Indian state of Uttar Pradesh, known historically for its trade and cultural significance.
  • 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_69ca83e467108190abcae6a33b3d4dad completed March 30, 2026, 2:08 p.m.
NER Named-entity recognition batch_69ccbfa128d48190b54b8f95d77d81cc completed April 1, 2026, 6:48 a.m.
NED1 Entity disambiguation (via context triple) batch_69d054a36ef881908079558050c67e7c completed April 4, 2026, midnight
Created at: March 30, 2026, 7:23 p.m.