Triple

T15057354
Position Surface form Disambiguated ID Type / Status
Subject Patna division E379529 entity
Predicate containsCity P294 FINISHED
Object Buxar E228633 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: Buxar | Statement: [Patna division, containsCity, Buxar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buxar
Context triple: [Patna division, containsCity, Buxar]
  • A. Buxar chosen
    Buxar is a historic town in the Indian state of Bihar, best known as the site of a pivotal 1764 battle that cemented British colonial dominance in northern India.
  • B. Darbhanga
    Darbhanga is a major city in the Indian state of Bihar, known as a cultural and educational center of the Mithila region.
  • C. Karimganj
    Karimganj is a town in the Indian state of Assam, known as a commercial and administrative center near the India–Bangladesh border.
  • D. Jangipur
    Jangipur is a town in the Murshidabad district of the Indian state of West Bengal, known for its administrative significance and proximity to the Ganges River.
  • E. Bikapur
    Bikapur is a town and administrative subdivision in the Ayodhya district of Uttar Pradesh, India, known for its proximity to the historic city of Ayodhya.
  • 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_69d85cd64d108190853797a95c11cc45 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69deda937f788190899d81bbb2084443 completed April 15, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69feae0fd7dc8190a10c8eb7542c3088 completed May 9, 2026, 3:46 a.m.
Created at: April 10, 2026, 3:01 a.m.