Triple

T13852677
Position Surface form Disambiguated ID Type / Status
Subject West Champaran district E332982 entity
Predicate hasTown P847 FINISHED
Object Narkatiaganj E1064965 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: Narkatiaganj | Statement: [West Champaran district, hasTown, Narkatiaganj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Narkatiaganj
Context triple: [West Champaran district, hasTown, Narkatiaganj]
  • A. Narkatiaganj chosen
    Narkatiaganj is a town and legislative assembly constituency in the West Champaran district of Bihar, India.
  • B. Keraniganj
    Keraniganj is a suburban upazila of Dhaka, Bangladesh, known for its dense population, river-based commerce, and numerous garment and brick industries.
  • C. Nawabganj
    Nawabganj is a town in the Indian state of Uttar Pradesh, known as one of the urban centers within Barabanki district.
  • D. Rairangpur
    Rairangpur is a town and legislative assembly constituency in the Mayurbhanj district of Odisha, India, known as the political base of President Droupadi Murmu.
  • E. Karimganj
    Karimganj is a town in the Indian state of Assam, known as a commercial and administrative center near the India–Bangladesh border.
  • 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_69d81c5ba13c8190839315f54768acfd completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02da9460819093a3ec5a3c62ea81 completed April 14, 2026, 9:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7c0f73838819085d6f052c00fc494 completed May 3, 2026, 9:41 p.m.
Created at: April 9, 2026, 10:14 p.m.