Triple

T12375799
Position Surface form Disambiguated ID Type / Status
Subject Bihar Sharif E295118 entity
Predicate historicalName P65 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: [Bihar Sharif, historicalName, Bihar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bihar
Context triple: [Bihar Sharif, historicalName, 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. Bihar
    Bihar is a historical region in Central Europe that once formed part of the Kingdom of Hungary and now lies divided mainly between eastern Hungary and western Romania.
  • C. Jharkhand
    Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
  • D. 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.
  • E. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fb8d6c081909e8bbbd52c73f29c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f63ef6084c8190960f0df7e10066e2 completed May 2, 2026, 6:14 p.m.
Created at: April 8, 2026, 9:54 p.m.