Triple

T17108769
Position Surface form Disambiguated ID Type / Status
Subject Jiuquan E415169 entity
Predicate borderedBy P224 FINISHED
Object Zhangye E469630 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: Zhangye | Statement: [Jiuquan, borderedBy, Zhangye]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Zhangye
Context triple: [Jiuquan, borderedBy, Zhangye]
  • A. Zhangye chosen
    Zhangye is a historic city in northwestern China, known for its location on the ancient Silk Road and its colorful Danxia landform landscapes.
  • B. Yumen City
    Yumen City is a county-level city in Gansu Province, China, historically known as an important stop along the ancient Silk Road and for its oil industry.
  • C. Tianshui
    Tianshui is a historic city in eastern Gansu Province, China, known as an important stop on the ancient Silk Road and for its nearby Maijishan Grottoes.
  • D. Yecheng
    Yecheng was an important ancient Chinese city that served as a major political and cultural center in northern China during several dynasties.
  • E. Golmud
    Golmud is a major industrial and transportation hub city in western China, located on the Qinghai-Tibet Plateau and serving as a key gateway to Tibet.
  • 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_69d886d090cc8190a39cb94992586905 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3dc2906a081909d0d43cf04319f52 completed April 18, 2026, 7:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a015fbff4b48190970073eb3b9d5d75 completed May 11, 2026, 4:49 a.m.
Created at: April 10, 2026, 5:35 a.m.