Triple

T22602735
Position Surface form Disambiguated ID Type / Status
Subject Edward Cole E574870 entity
Predicate hasSceneLocation P124600 FINISHED
Object Mount Everest 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: Mount Everest | Statement: [Edward Cole, hasSceneLocation, Mount Everest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mount Everest
Context triple: [Edward Cole, hasSceneLocation, Mount Everest]
  • A. Mount Everest chosen
    Mount Everest is the world's highest mountain above sea level, located in the Himalayas on the border between Nepal and the Tibet Autonomous Region of China.
  • B. Everest
    Everest is the codename for the high-performance CPU cores used in Apple’s A16 Bionic chip.
  • C. Everest
    Everest is a snow rescue pup from the animated children's series PAW Patrol, known for her bravery, love of the snow, and role as the team's mountain rescue specialist.
  • D. Everest
    Everest is a 2015 survival drama film that chronicles the harrowing true story of a deadly Mount Everest expedition.
  • E. Cho Oyu
    Cho Oyu is the world’s sixth-highest mountain, an 8,188-meter peak in the Mahalangur Himal section of the Himalayas near the Nepal–China border.
  • 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1626eb178819096866d03a78f82fc completed April 29, 2026, 1:44 a.m.
Created at: April 17, 2026, 2:50 p.m.