Triple

T7864967
Position Surface form Disambiguated ID Type / Status
Subject Himadri E182592 entity
Predicate hasPeak P8205 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: [Himadri, hasPeak, Makalu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Makalu
Context triple: [Himadri, hasPeak, 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_69ca82894d9081908a832bfce71a4714 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb36c0eaa48190a0df4c37c726546e completed March 31, 2026, 2:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf51147c4c8190b3c893700f48fc54 completed April 3, 2026, 5:33 a.m.
Created at: March 30, 2026, 4:54 p.m.