Triple

T19721897
Position Surface form Disambiguated ID Type / Status
Subject Nagpur district E473628 entity
Predicate bordersDistrict P224 FINISHED
Object Bhandara district NE NERFINISHED

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: Bhandara district | Statement: [Nagpur district, bordersDistrict, Bhandara district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bhandara district
Context triple: [Nagpur district, bordersDistrict, Bhandara district]
  • A. Bhandara district chosen
    Bhandara district is an administrative district in the Indian state of Maharashtra, located in the Vidarbha region and known for its rice production and lakes.
  • B. Ganjam district
    Ganjam district is a coastal administrative region in the Indian state of Odisha, known for its rich cultural heritage, distinctive Odia dialects, and historical significance.
  • C. Hoshangabad district
    Hoshangabad district is an administrative region in the central Indian state of Madhya Pradesh, known for its agricultural landscape along major rivers and its proximity to the Satpura hill ranges.
  • D. Gaj district
    Gaj district is a residential neighborhood in the city of Wrocław, Poland.
  • E. Babu District
    Babu District is an urban district and key administrative area within the prefecture-level city of Hezhou in Guangxi, China.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e516dd048190a0b6c93ea3e71f58 completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e649f587d88190bf519fec7ce634d3 completed April 20, 2026, 3:44 p.m.
Created at: April 10, 2026, 1:46 p.m.