Triple

T13514289
Position Surface form Disambiguated ID Type / Status
Subject Ramgarh E322717 entity
Predicate locatedIn P40 FINISHED
Object Jharkhand E61121 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: Jharkhand | Statement: [Ramgarh, locatedIn, Jharkhand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jharkhand
Context triple: [Ramgarh, locatedIn, Jharkhand]
  • A. Jharkhand chosen
    Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
  • B. Bihar
    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.
  • C. 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.
  • 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. 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.
  • 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_69d80766a21881909f21a1b7421d3b8a completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaf87ca288190a147fbdb2f90985f completed April 12, 2026, 2:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69f78ad8903c8190afbf15234a81d657 completed May 3, 2026, 5:50 p.m.
Created at: April 9, 2026, 9:44 p.m.