Triple
T3974456
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Citroën C5 |
E85605
|
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: [Citroën C5, assemblyLocation, Wuhan, China]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wuhan, China Context triple: [Citroën C5, 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_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9b511f88190afca12c77481b344 |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5401712188190aa6144dc1d5dcab6 |
completed | March 14, 2026, 11:01 a.m. |
Created at: March 9, 2026, 3:32 p.m.