Triple

T16653634
Position Surface form Disambiguated ID Type / Status
Subject Mount Victoria E404668 entity
Predicate nearestTown P350 FINISHED
Object Kanpetlet E797242 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: Kanpetlet | Statement: [Mount Victoria, nearestTown, Kanpetlet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kanpetlet
Context triple: [Mount Victoria, nearestTown, Kanpetlet]
  • A. Kanpetlet chosen
    Kanpetlet is a small, remote town in western Myanmar known as a gateway to Nat Ma Taung (Mount Victoria) and its surrounding national park.
  • B. Toyapakeh
    Toyapakeh is a renowned dive site off Nusa Penida in Bali, Indonesia, known for its rich coral reefs, clear waters, and diverse marine life including manta rays and mola mola.
  • C. Kuto-Kute
    Kuto-Kute is a regional dialect of the Sasak language spoken by Sasak communities on the island of Lombok in Indonesia.
  • D. Kanpa
    Kanpa is a small remote Aboriginal community located within Western Australia’s Shire of Ngaanyatjarraku.
  • E. Bakoteh
    Bakoteh is a residential neighborhood within the urban area of Serekunda in The Gambia.
  • 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_69d8838b5fbc81908c6575c132b82e80 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e37bf861348190b2b0b5574d4ddb4f completed April 18, 2026, 12:41 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0084c6bf8c81909b376875ae038e3f completed May 10, 2026, 1:14 p.m.
Created at: April 10, 2026, 5:18 a.m.