Triple

T12074722
Position Surface form Disambiguated ID Type / Status
Subject Yunnan–Guizhou Plateau E287515 entity
Predicate hasCity P316 FINISHED
Object Qujing E211404 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: Qujing | Statement: [Yunnan–Guizhou Plateau, hasCity, Qujing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Qujing
Context triple: [Yunnan–Guizhou Plateau, hasCity, Qujing]
  • A. Qujing chosen
    Qujing is a major prefecture-level city in eastern Yunnan Province, China, known as an important regional transportation and industrial hub.
  • B. Dongjing
    Dongjing is the historical name for Kaifeng when it served as the capital of the Northern Song dynasty in China.
  • C. Wulou
    Wulou is the traditional name for Zhenhai Tower, a historic multi-story landmark in Guangzhou, China, known for its commanding views and cultural significance.
  • D. Jingnan
    Jingnan was a small regional kingdom in south-central China that existed during the Five Dynasties and Ten Kingdoms period.
  • E. Licheng
    Licheng is the courtesy name of the Daoguang Emperor, a Qing dynasty ruler of China in the early 19th century.
  • 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_69d6ab4846e081908ee7bbd66a6d3459 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9045bbc508190abf6e3316701e587 completed April 10, 2026, 2:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60a683a108190b8f05c40ecda5f0e completed May 2, 2026, 2:30 p.m.
Created at: April 8, 2026, 9:48 p.m.