Triple

T13294397
Position Surface form Disambiguated ID Type / Status
Subject Madhepura E316642 entity
Predicate locatedIn P40 FINISHED
Object Madhepura district E253828 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: Madhepura district | Statement: [Madhepura, locatedIn, Madhepura district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madhepura district
Context triple: [Madhepura, locatedIn, Madhepura district]
  • A. Madhepura district chosen
    Madhepura district is an administrative district in the Indian state of Bihar, known for its agrarian economy and location in the flood-prone Kosi river region.
  • B. Madhepura
    Madhepura is a town and district headquarters in the eastern Indian state of Bihar, known for its agricultural economy and regional administrative importance.
  • C. Bhadohi district
    Bhadohi district is a district in the Indian state of Uttar Pradesh, widely known as a major center for carpet weaving and textile production.
  • D. Bhagalpur district
    Bhagalpur district is an administrative region in the state of Bihar, India, known for its historic city of Bhagalpur and its traditional silk industry.
  • E. Kaimur district
    Kaimur district is an administrative region in the Indian state of Bihar, known for its rugged terrain, forested hills, and rich archaeological and cultural heritage.
  • 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_69d806b349908190a9a61dd9323bf153 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d99079c8508190b6208db9affcbc0e completed April 11, 2026, 12:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69f716d8ee2081908428339216c43b47 completed May 3, 2026, 9:35 a.m.
Created at: April 9, 2026, 9:28 p.m.