Triple

T3641427
Position Surface form Disambiguated ID Type / Status
Subject Changping District E77195 entity
Predicate capital P234 FINISHED
Object Changping E77195 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: Changping | Statement: [Changping District, capital, Changping]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Changping
Context triple: [Changping District, capital, Changping]
  • A. Lingang
    Lingang is a rapidly developing industrial and high-tech district in Shanghai, China, known for hosting major manufacturing facilities such as Tesla’s Gigafactory Shanghai.
  • B. Yizhuang
    Yizhuang is a rapidly developing suburban area in southeastern Beijing known for its economic and technological development zone and growing residential communities.
  • C. Changping District chosen
    Changping District is a suburban district in the northern part of Beijing, China, known for its historical sites and scenic mountainous landscapes.
  • D. Daoxin
    Daoxin was an influential early Chinese Chan (Zen) Buddhist master traditionally regarded as the Fourth Patriarch, known for helping shape the school’s meditative and doctrinal foundations.
  • E. Chaoyang
    Chaoyang is a prefecture-level city in western Liaoning Province, China, known for its historical sites and role as a regional transportation and agricultural center.
  • 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_69ad85de1b988190a45f8dbfebc806fc completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc357c3308190bd8801d68244a53e completed March 8, 2026, 6:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69be031d16a08190b84524b7153f7f85 completed March 21, 2026, 2:31 a.m.
Created at: March 8, 2026, 3:24 p.m.