Triple

T22443449
Position Surface form Disambiguated ID Type / Status
Subject Bhagalpur region E554810 entity
Predicate hasPart P35 FINISHED
Object Bhagalpur city 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: Bhagalpur city | Statement: [Bhagalpur region, hasPart, Bhagalpur city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhagalpur city
Context triple: [Bhagalpur region, hasPart, Bhagalpur city]
  • A. Bhagalpur chosen
    Bhagalpur is a historic city in the eastern Indian state of Bihar, known for its silk industry and location along the Ganges River.
  • B. Muzaffarpur
    Muzaffarpur is a major city in northern India known for its litchi production and role as an important commercial and educational center in the region.
  • C. Purnia
    Purnia is a major city in northeastern India known as a commercial and agricultural hub of the Seemanchal region.
  • D. Samastipur
    Samastipur is a city in the Indian state of Bihar known as an important railway junction and agricultural trade center in the region.
  • E. Gorakhpur
    Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
  • 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_69e11e5010e48190ae1e9c9db9697637 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15ae40f9081908674015beb33f74e completed April 29, 2026, 1:12 a.m.
Created at: April 16, 2026, 8:47 p.m.