Triple

T9639208
Position Surface form Disambiguated ID Type / Status
Subject Lionel Terray E233016 entity
Predicate climbed P6287 FINISHED
Object Makalu E34016 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: Makalu | Statement: [Lionel Terray, climbed, Makalu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makalu
Context triple: [Lionel Terray, climbed, Makalu]
  • A. Makalu chosen
    Makalu is the fifth-highest mountain in the world, a prominent 8,485-meter peak on the border between Nepal and China known for its steep faces and challenging climbing routes.
  • B. Kangchenjunga
    Kangchenjunga is the world’s third-highest mountain, a massive peak in the eastern Himalayas on the border between Nepal and India.
  • C. 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.
  • D. Shishapangma
    Shishapangma is one of the world’s fourteen eight-thousanders, a major Himalayan peak located entirely within Tibet, China.
  • E. Lhotse
    Lhotse is the world’s fourth-highest mountain, located near Mount Everest in the Himalayas on the border between Nepal and the Tibet Autonomous Region of China.
  • 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_69ca848a5a908190aad251f4137b0c3a completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9b532aa4819087b56be6f5635126 completed April 1, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69d354af200881909b08ab9b71d0d53f completed April 6, 2026, 6:37 a.m.
Created at: March 30, 2026, 8:12 p.m.