Triple

T7660151
Position Surface form Disambiguated ID Type / Status
Subject Bidesia theatre E173483 entity
Predicate originatesFrom P26 FINISHED
Object Bihar E60958 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: Bihar | Statement: [Bidesia theatre, originatesFrom, Bihar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bihar
Context triple: [Bidesia theatre, originatesFrom, Bihar]
  • A. Bihar chosen
    Bihar is a populous state in eastern India known for its rich historical heritage, including ancient centers of learning like Nalanda and significant sites in Buddhist history.
  • B. Jharkhand
    Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
  • C. Madhya Pradesh
    Madhya Pradesh is a large central Indian state known for its historical cities, diverse tribal cultures, and significant forested and wildlife areas including several major national parks.
  • D. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • E. West Bengal
    West Bengal is an eastern Indian state known for its cultural heritage, literature, and the metropolis of Kolkata (formerly Calcutta).
  • 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_69c69955517c819085bc715b96d304d2 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c701a47a5c8190867e39f552c86787 completed March 27, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8eef3b7a88190bb42b5f93ce2daba completed March 29, 2026, 9:20 a.m.
Created at: March 27, 2026, 3:59 p.m.