Triple

T13804260
Position Surface form Disambiguated ID Type / Status
Subject Azamgarh district E331719 entity
Predicate hasVidhanSabhaConstituency P23217 FINISHED
Object Mubarakpur E1080803 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: Mubarakpur | Statement: [Azamgarh district, hasVidhanSabhaConstituency, Mubarakpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mubarakpur
Context triple: [Azamgarh district, hasVidhanSabhaConstituency, Mubarakpur]
  • A. Mubarakpur chosen
    Mubarakpur is a town in Uttar Pradesh, India, known for its traditional handloom weaving and production of fine silk sarees.
  • B. Zaidpur
    Zaidpur is a town in the Barabanki district of Uttar Pradesh, India, known for its local markets and traditional crafts.
  • C. Mominpura
    Mominpura is a locality in Nagpur, Maharashtra, India, known as a densely populated residential and commercial area with a significant Muslim community.
  • D. Akbarpur
    Akbarpur is a town in the Indian state of Uttar Pradesh known as the birthplace of socialist leader Ram Manohar Lohia.
  • E. Babatpur
    Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
  • 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_69d81c59f8808190a851bc56afdc55e9 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de026c36108190a7436034a730a261 completed April 14, 2026, 9:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69fd192957008190b525778430b56ca0 completed May 7, 2026, 10:58 p.m.
Created at: April 9, 2026, 10:12 p.m.