Triple

T20130438
Position Surface form Disambiguated ID Type / Status
Subject Burhanpur railway station E490873 entity
Predicate connectsTo P845 FINISHED
Object Bhusawal 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: Bhusawal | Statement: [Burhanpur railway station, connectsTo, Bhusawal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhusawal
Context triple: [Burhanpur railway station, connectsTo, Bhusawal]
  • A. Bhusawal chosen
    Bhusawal is a major railway and commercial city in Maharashtra, India, known for its large railway junction and banana-growing region.
  • B. Baramati
    Baramati is a town in the Pune district of Maharashtra, India, known as an agricultural and industrial hub with historical and political significance.
  • C. Chandwad
    Chandwad is a town in the Nashik district of Maharashtra, India, known for its historical temples and hill forts.
  • D. Warora
    Warora is a town in Maharashtra, India, known historically for its coal mining and industrial activities within the Chandrapur district.
  • E. Ratlam
    Ratlam is a prominent commercial city in western Madhya Pradesh, India, known for its railway junction, textile and chemical industries, and production of gold and silver jewelry.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676183dc8190b65d0def681aaa1e completed April 20, 2026, 5:50 p.m.
Created at: April 11, 2026, 11:31 p.m.