Triple
T15974734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Liu |
E387414
|
entity |
| Predicate | parent |
P120
|
FINISHED |
| Object | Liu Chuanzhi |
E356432
|
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: Liu Chuanzhi | Statement: [Jean Liu, parent, Liu Chuanzhi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Liu Chuanzhi Context triple: [Jean Liu, parent, Liu Chuanzhi]
-
A.
Liu Chuanzhi
chosen
Liu Chuanzhi is a Chinese entrepreneur best known as the founder and longtime leader of Lenovo, which he built into one of the world’s largest personal computer manufacturers.
-
B.
Wang Chuanfu
Wang Chuanfu is a Chinese entrepreneur and engineer best known as the billionaire founder and chairman of electric vehicle and battery giant BYD.
-
C.
Ren Zhengfei
Ren Zhengfei is a Chinese entrepreneur best known as the founder and longtime leader of the telecommunications giant Huawei Technologies.
-
D.
Lei Jun
Lei Jun is a Chinese entrepreneur and billionaire best known as the co-founder and CEO of the electronics and technology company Xiaomi.
-
E.
Zhang Ruimin
Zhang Ruimin is a prominent Chinese business executive best known for transforming Haier into a leading global home appliance and electronics brand.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1572c216c81908f2070d2a87609c2 |
completed | April 16, 2026, 9:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffbe8ce7788190a3e0aefc9a29d58a |
completed | May 9, 2026, 11:09 p.m. |
Created at: April 10, 2026, 4:54 a.m.