Triple

T13610960
Position Surface form Disambiguated ID Type / Status
Subject Coorg E325184 entity
Predicate partOf P40 FINISHED
Object Mysore Division E1034277 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: Mysore Division | Statement: [Coorg, partOf, Mysore Division]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mysore Division
Context triple: [Coorg, partOf, Mysore Division]
  • A. Mysuru division chosen
    Mysuru division is an administrative division in the Indian state of Karnataka that encompasses Mysuru district and several neighboring districts for regional governance.
  • B. Hyderabad Division
    Hyderabad Division is an administrative division in the Sindh province of Pakistan that encompasses the city of Hyderabad and surrounding districts.
  • C. Benares Division
    Benares Division was an administrative division centered around the historic city of Benares (Varanasi) in British India’s North-Western Provinces.
  • D. Shimoga division
    Shimoga division is an administrative division in the Indian state of Karnataka, centered around the city of Shivamogga and encompassing several surrounding districts and towns.
  • E. Vellore division
    Vellore division is an administrative revenue division in the Vellore district of the Indian state of Tamil Nadu.
  • 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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbb0aa9a1481908c6f92495aff86c6 completed April 12, 2026, 2:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77f9a9f9c81909b0a8f4f51c461ae completed May 3, 2026, 5:02 p.m.
Created at: April 9, 2026, 9:50 p.m.