Triple

T7784780
Position Surface form Disambiguated ID Type / Status
Subject Bhagalpur E187213 entity
Predicate historicalName P65 FINISHED
Object Bhagalpur City E187213 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: Bhagalpur City | Statement: [Bhagalpur, historicalName, Bhagalpur City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhagalpur City
Context triple: [Bhagalpur, historicalName, 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 (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_69ca82af2d2c8190963861f5e0b8bf21 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cadf210f508190b215a0ab95192689 completed March 30, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_69cb139059a08190a8a4df25ee09756b completed March 31, 2026, 12:21 a.m.
Created at: March 30, 2026, 4:23 p.m.