Triple

T12789081
Position Surface form Disambiguated ID Type / Status
Subject Berar E305708 entity
Predicate historicalCapital P2536 FINISHED
Object Ellichpur E461985 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: Ellichpur | Statement: [Berar, historicalCapital, Ellichpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ellichpur
Context triple: [Berar, historicalCapital, Ellichpur]
  • A. Ellichpur chosen
    Ellichpur is a historic city in Maharashtra, India, that once served as an important regional capital under the Deccan sultanates.
  • B. Karanpur
    Karanpur is a town located in the Ganganagar district of the northern Indian state of Rajasthan.
  • C. Jagdishpur
    Jagdishpur is a town in the Bhojpur district of Bihar, India, historically known as the ancestral estate of the 19th-century freedom fighter Kunwar Singh.
  • D. Vikrampur
    Vikrampur was a historic urban and political center in the Bengal region, renowned as an important seat of power and culture in medieval South Asia.
  • E. Partapur
    Partapur is a locality in Meerut district of Uttar Pradesh, India, known for its proximity to the Dr. Bhimrao Ambedkar Airstrip and its growing urban and institutional development.
  • 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_69d7bdf366888190a8cccb982606889c completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e6a61f48190972e241e70bc392c completed April 10, 2026, 9:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6d5ed774881909d2df630820e5f21 completed May 3, 2026, 4:58 a.m.
Created at: April 9, 2026, 5:30 p.m.