Triple

T22157822
Position Surface form Disambiguated ID Type / Status
Subject Altyn Tagh Fault E547586 entity
Predicate adjacentTo P224 FINISHED
Object Kunlun Shan NE NERFINISHED

How this triple was built (3 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: Kunlun Shan | Statement: [Altyn Tagh Fault, adjacentTo, Kunlun Shan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kunlun Shan
Context triple: [Altyn Tagh Fault, adjacentTo, Kunlun Shan]
  • A. Chihsing Mountain
    Chihsing Mountain is a volcanic peak in Yangmingshan National Park near Taipei, Taiwan, known as the highest mountain in the Taipei area and a popular hiking destination.
  • B. Qilai Mountain
    Qilai Mountain is a prominent and rugged peak in Taiwan’s Central Mountain Range, known for its dramatic cliffs, challenging hiking routes, and frequent foggy, atmospheric conditions.
  • C. Nenggao Mountain
    Nenggao Mountain is a prominent high peak in Taiwan known for its challenging hiking routes and scenic alpine landscapes within the Central Mountain Range.
  • D. Mount Song
    Mount Song is one of China’s Five Great Mountains, renowned as a sacred Taoist and Buddhist site that hosts ancient temples, academies, and other historic monuments around Dengfeng.
  • E. Qílián Shān
    Qílián Shān refers to the Qilian Mountains, a major mountain range in northern China forming part of the northeastern edge of the Tibetan Plateau.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kunlun Shan
Target entity description: Kunlun Shan is a major mountain range in western China forming part of the northern edge of the Tibetan Plateau and known for its high, rugged peaks and geological significance.
  • A. Chihsing Mountain
    Chihsing Mountain is a volcanic peak in Yangmingshan National Park near Taipei, Taiwan, known as the highest mountain in the Taipei area and a popular hiking destination.
  • B. Qilai Mountain
    Qilai Mountain is a prominent and rugged peak in Taiwan’s Central Mountain Range, known for its dramatic cliffs, challenging hiking routes, and frequent foggy, atmospheric conditions.
  • C. Nenggao Mountain
    Nenggao Mountain is a prominent high peak in Taiwan known for its challenging hiking routes and scenic alpine landscapes within the Central Mountain Range.
  • D. Mount Song
    Mount Song is one of China’s Five Great Mountains, renowned as a sacred Taoist and Buddhist site that hosts ancient temples, academies, and other historic monuments around Dengfeng.
  • E. Qílián Shān
    Qílián Shān refers to the Qilian Mountains, a major mountain range in northern China forming part of the northeastern edge of the Tibetan Plateau.
  • F. None of above. chosen

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_69e11e3b52088190ad5df386d01eb2fb completed April 16, 2026, 5:36 p.m.
NER Named-entity recognition batch_69f12a2aadb48190b4d739d1df9529db completed April 28, 2026, 9:44 p.m.
Created at: April 16, 2026, 8:33 p.m.