Triple

T20182246
Position Surface form Disambiguated ID Type / Status
Subject Badshahi Qila, Burhanpur E492757 entity
Predicate locatedIn P40 FINISHED
Object Burhanpur 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: Burhanpur | Statement: [Badshahi Qila, Burhanpur, locatedIn, Burhanpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Burhanpur
Context triple: [Badshahi Qila, Burhanpur, locatedIn, Burhanpur]
  • A. Burhanpur chosen
    Burhanpur is a historic city in central India known for its Mughal-era architecture and strategic location on the banks of the Tapti River.
  • B. Baharampur
    Baharampur is a major town and administrative center in the Murshidabad district of the Indian state of West Bengal, known for its historical significance and regional commerce.
  • C. Narayanpur
    Narayanpur is a town located in the Lakhimpur district of the Indian state of Assam.
  • D. Babatpur
    Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
  • E. Mahidpur
    Mahidpur is a historic town in the Indian state of Madhya Pradesh, known for its location in the Malwa region and its role in the Anglo-Maratha conflicts.
  • 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_69da6268a034819081cbd9ea5a1c9475 completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e668ef9370819091a8479f811002a9 completed April 20, 2026, 5:57 p.m.
Created at: April 11, 2026, 11:36 p.m.