Triple

T1583343
Position Surface form Disambiguated ID Type / Status
Subject Makalu E34016 entity
Predicate near P350 FINISHED
Object Lhotse E33536 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: Lhotse | Statement: [Makalu, near, Lhotse]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lhotse
Context triple: [Makalu, near, Lhotse]
  • A. Lhotse chosen
    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.
  • B. 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.
  • C. Manaslu
    Manaslu is the eighth-highest mountain in the world, a prominent 8,000-meter peak in the Nepalese Himalayas renowned for its challenging climbing routes and dramatic ridgelines.
  • D. Kangchenjunga
    Kangchenjunga is the world’s third-highest mountain, a massive peak in the eastern Himalayas on the border between Nepal and India.
  • E. Makalu
    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.
  • 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_69a885fceb2c8190b47e0f7c0aefbff0 completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a908f0e72c8190bb7a2a0c77379060 completed March 5, 2026, 4:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69ada967e01481908802baf2de7ad6a7 completed March 8, 2026, 4:52 p.m.
Created at: March 4, 2026, 7:27 p.m.