Triple

T18279243
Position Surface form Disambiguated ID Type / Status
Subject Moradabad division E437819 entity
Predicate hasMajorCity P316 FINISHED
Object Bijnor 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: Bijnor | Statement: [Moradabad division, hasMajorCity, Bijnor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bijnor
Context triple: [Moradabad division, hasMajorCity, Bijnor]
  • A. Bijnor chosen
    Bijnor is a prominent city in the Indian state of Uttar Pradesh, known for its agricultural economy, especially sugarcane cultivation, and its historical and cultural significance in the region.
  • B. Manbij
    Manbij is a strategically important, ethnically diverse city in northern Syria that has served as a key political and military hub within the Autonomous Administration of North and East Syria.
  • C. Jagiroad
    Jagiroad is a prominent industrial and commercial town in Assam, India, known especially for its paper mill and strategic location along key transport routes.
  • D. Bargachia
    Bargachia is a small town in the Howrah district of West Bengal, India, known as a suburban locality within the Kolkata metropolitan region.
  • E. Kasarani
    Kasarani is a residential and commercial suburb in northeastern Nairobi, Kenya, known for hosting major sports and educational facilities.
  • 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_69d8b914530c8190b4474d862a2b2a1b completed April 10, 2026, 8:47 a.m.
NER Named-entity recognition batch_69e50054d1dc8190b31d02f617256e9d completed April 19, 2026, 4:18 p.m.
Created at: April 10, 2026, 10:34 a.m.