Triple

T13154291
Position Surface form Disambiguated ID Type / Status
Subject Vaishali district E312543 entity
Predicate hasHeadquarters P62 FINISHED
Object Hajipur E308384 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: Hajipur | Statement: [Vaishali district, hasHeadquarters, Hajipur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hajipur
Context triple: [Vaishali district, hasHeadquarters, Hajipur]
  • A. Hajipur chosen
    Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
  • B. Bhadohi
    Bhadohi is a city in Uttar Pradesh, India, renowned as a major center for carpet weaving and often referred to as the "Carpet City" of the country.
  • C. Saharanpur
    Saharanpur is a city in the Indian state of Uttar Pradesh known as a commercial and transportation hub, particularly for its wood carving industry and agricultural trade.
  • D. Sasaram
    Sasaram is a historic town in eastern India known for its grand Mughal-era monuments, especially the tomb of Sher Shah Suri.
  • E. Chhapra
    Chhapra is a city in the Indian state of Bihar, known as the administrative headquarters of Saran district and a regional commercial and transportation hub along the Ganges River.
  • 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_69d806aabde48190899e13e41659cae5 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69d98c06ccb881909390df18e1a6f7ed completed April 10, 2026, 11:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7460c05bc819089cdd004bb07c492 completed May 3, 2026, 12:56 p.m.
Created at: April 9, 2026, 9:11 p.m.