Triple

T8760932
Position Surface form Disambiguated ID Type / Status
Subject Bhilai E208195 entity
Predicate locatedIn P40 FINISHED
Object Durg district E662177 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: Durg district | Statement: [Bhilai, locatedIn, Durg district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Durg district
Context triple: [Bhilai, locatedIn, Durg district]
  • A. Durg district chosen
    Durg district is an administrative district in the state of Chhattisgarh, India, known for its industrial development and urban centers such as the city of Durg.
  • B. Sidhi district
    Sidhi district is an administrative district in the Indian state of Madhya Pradesh, known for its coal mining areas and part of the Singrauli region.
  • C. Narmada district
    Narmada district is an administrative district in the state of Gujarat, India, known for the Narmada River and the Statue of Unity near Kevadia.
  • D. Satna district
    Satna district is an administrative district in the Indian state of Madhya Pradesh, known for its cement industries and proximity to important historical and religious sites.
  • E. Dantewada district
    Dantewada district is a mineral-rich, predominantly tribal district in the southern part of Chhattisgarh, India, known for both its dense forests and its history of Maoist insurgency.
  • 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_69ca835df7e08190ac875664cca8f9ca completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5df9729481908679151988b76d2f completed March 31, 2026, 11:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf434bcac08190be07175a26804185 completed April 3, 2026, 4:34 a.m.
Created at: March 30, 2026, 6:40 p.m.