Triple

T17032678
Position Surface form Disambiguated ID Type / Status
Subject Silver City E413237 entity
Predicate locatedIn P40 FINISHED
Object Odisha E76751 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: Odisha | Statement: [Silver City, locatedIn, Odisha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Odisha
Context triple: [Silver City, locatedIn, Odisha]
  • A. Orissa chosen
    Orissa is a historical region and modern Indian state on the eastern coast of India, known for its rich cultural heritage, ancient temples, and significant role in the subcontinent’s political and economic history.
  • B. Chhattisgarh
    Chhattisgarh is a state in central India known for its rich mineral resources, dense forests, tribal cultures, and growing industrial and power sectors.
  • C. Jharkhand
    Jharkhand is an eastern Indian state known for its rich mineral resources, significant tribal population, and extensive forests and plateaus.
  • D. West Bengal
    West Bengal is an eastern Indian state known for its cultural heritage, literature, and the metropolis of Kolkata (formerly Calcutta).
  • E. Andhra Pradesh
    Andhra Pradesh is a state in southeastern India known for its long coastline along the Bay of Bengal, Telugu-speaking population, and major cities such as Visakhapatnam and Vijayawada.
  • 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_69d886cd18288190b006abab23f811b7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d8ed79448190a750a29a99913fda completed April 18, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0139ef70208190b26029511e91afb0 completed May 11, 2026, 2:07 a.m.
Created at: April 10, 2026, 5:33 a.m.