Triple

T22384237
Position Surface form Disambiguated ID Type / Status
Subject Bardhaman Municipality E553353 entity
Predicate cityServed P82 FINISHED
Object Bardhaman 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: Bardhaman | Statement: [Bardhaman Municipality, cityServed, Bardhaman]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bardhaman
Context triple: [Bardhaman Municipality, cityServed, Bardhaman]
  • A. Barpeta
    Barpeta is a town in the Indian state of Assam known for its historical Barpeta Satra and cultural significance in the Vaishnavite tradition.
  • B. Chandanagar
    Chandanagar is a residential and commercial suburb in the northwestern part of Hyderabad, India, known for its proximity to IT hubs and growing urban infrastructure.
  • C. Burdwan chosen
    Burdwan is a historic city in the Indian state of West Bengal, known for its cultural heritage, educational institutions, and former status as a major administrative and commercial center.
  • D. Malda
    Malda is a town in eastern India known as a commercial hub and historic gateway to the northern districts of West Bengal.
  • E. Kharagpur
    Kharagpur is an industrial city in eastern India best known for hosting the first campus of the Indian Institute of Technology (IIT Kharagpur) and one of the country’s longest railway platforms.
  • 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_69e11e4cf87c8190a1ff474daec326b7 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f1582e58dc8190a2ad6b10c9d1f951 completed April 29, 2026, 1 a.m.
Created at: April 16, 2026, 8:45 p.m.