Triple

T13661789
Position Surface form Disambiguated ID Type / Status
Subject Ambedkar Nagar district E327014 entity
Predicate hasUrbanCenters P11388 FINISHED
Object Akbarpur E288606 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: Akbarpur | Statement: [Ambedkar Nagar district, hasUrbanCenters, Akbarpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Akbarpur
Context triple: [Ambedkar Nagar district, hasUrbanCenters, Akbarpur]
  • A. Akbarpur chosen
    Akbarpur is a town in the Indian state of Uttar Pradesh known as the birthplace of socialist leader Ram Manohar Lohia.
  • B. Daryapur
    Daryapur is a town in the Amravati district of Maharashtra, India, known for its agricultural economy and regional market activities.
  • C. Sikandarpur
    Sikandarpur is a metro station in the Delhi Metro network that serves the Gurugram area and provides an interchange with the Rapid Metro system.
  • D. Mahipalpur
    Mahipalpur is an urban village and commercial area in Delhi, India, located near Indira Gandhi International Airport and known for its hotels, transport hubs, and proximity to major highways.
  • E. Gadarpur
    Gadarpur is a town in the Udham Singh Nagar district of Uttarakhand, India, known primarily as an agricultural and trading center in the Terai region.
  • 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_69d8076d8270819092afc2f0e9c359a8 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbc620df208190afaccf3ddd10aa60 completed April 12, 2026, 4:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69fba1b4ae588190b293c71312ee4037 completed May 6, 2026, 8:16 p.m.
Created at: April 9, 2026, 9:52 p.m.