Triple

T7834245
Position Surface form Disambiguated ID Type / Status
Subject Ngozumpa Glacier E181650 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Gokyo E187805 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: Gokyo | Statement: [Ngozumpa Glacier, hasNearbySettlement, Gokyo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gokyo
Context triple: [Ngozumpa Glacier, hasNearbySettlement, Gokyo]
  • A. Gokyo Ri
    Gokyo Ri is a popular trekking peak in Nepal’s Everest region, known for its panoramic views of Mount Everest, surrounding Himalayan giants, and the turquoise Gokyo Lakes.
  • B. Gyalshing
    Gyalshing is a town in the Indian state of Sikkim that serves as an important local commercial and administrative center in the region.
  • C. Gokyo Lakes chosen
    Gokyo Lakes is a high-altitude group of glacial lakes in Nepal’s Everest region, renowned for their turquoise waters, dramatic Himalayan scenery, and popularity among trekkers.
  • D. Gulmit
    Gulmit is a picturesque village in northern Pakistan’s Gilgit-Baltistan region, known for its traditional Wakhi culture, terraced fields, and views of the surrounding Karakoram peaks.
  • E. Jingpho
    Jingpho is a Tibeto-Burman language spoken primarily by the Jingpo people in parts of Myanmar, China, and India.
  • 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_69ca8284a25c8190a1a20afad30da792 completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb064a47648190af2ca2b336584a92 completed March 30, 2026, 11:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69cbdef32d4c8190a2e5c76d2db6c45f completed March 31, 2026, 2:49 p.m.
Created at: March 30, 2026, 4:45 p.m.