Triple

T4789546
Position Surface form Disambiguated ID Type / Status
Subject Peugeot 3008 E106567 entity
Predicate assemblyLocation P40 FINISHED
Object Wuhan, China E1680 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: Wuhan, China | Statement: [Peugeot 3008, assemblyLocation, Wuhan, China]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Wuhan, China
Context triple: [Peugeot 3008, assemblyLocation, Wuhan, China]
  • A. Wuhan chosen
    Wuhan is a major city in central China, known as a key industrial, commercial, and transportation hub located at the confluence of the Yangtze and Han rivers.
  • B. Port of Wuhan
    The Port of Wuhan is a major inland river port on the Yangtze River in central China, serving as a key hub for regional trade and transportation.
  • C. Shenzhen, China
    Shenzhen, China is a major southern Chinese metropolis known for its rapid transformation into a global technology and manufacturing hub bordering Hong Kong.
  • D. Huangshi
    Huangshi is an industrial city in eastern Hubei Province, China, known for its steel production and location along the Yangtze River.
  • E. Canton, China
    Canton, China is the former English name for Guangzhou, a major port city in southern China and the capital of Guangdong province.
  • 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_69bd43f4a9588190bf73e20bc27c03cc completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd65db847081908f5456724a2bdc65 completed March 20, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69be4d96f7e88190be4ba5c7ceb07608 completed March 21, 2026, 7:49 a.m.
Created at: March 20, 2026, 1:22 p.m.