Triple
T772063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SAIC Motor |
E16302
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | Wuling |
E2748
|
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: Wuling | Statement: [SAIC Motor, hasBrand, Wuling]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wuling Context triple: [SAIC Motor, hasBrand, Wuling]
-
A.
Wuling
chosen
Wuling is a Chinese automotive marque known for producing affordable compact cars and microvans, marketed through a joint venture involving General Motors.
-
B.
Chongxin
Chongxin is the Chinese given name of Joe Tsai, the Taiwanese-Canadian co-founder and executive vice chairman of Alibaba Group.
-
C.
Guanggu
Guanggu is a major high-tech development zone in Wuhan, China, known as an innovation hub for the optics and electronics industries.
-
D.
Changling
Changling is the largest and best-preserved mausoleum within Beijing’s Ming Tombs complex, built for the Yongle Emperor and his empress.
-
E.
Kaihui
Kaihui is a Chinese given name most notably borne by Yang Kaihui, the revolutionary and early partner of Mao Zedong.
- 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_69a49369a0848190af883934cee3db4c |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a706abf88190a1cbc2dfbbf9968a |
completed | March 1, 2026, 8:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7b83be4f88190ab5f969f4f52924e |
completed | March 4, 2026, 4:42 a.m. |
Created at: March 1, 2026, 7:37 p.m.