Triple
T10174121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nie Rongzhen |
E235806
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Rongzhen |
E116772
|
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: Rongzhen | Statement: [Nie Rongzhen, givenName, Rongzhen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rongzhen Context triple: [Nie Rongzhen, givenName, Rongzhen]
-
A.
Zhaoyuan
Zhaoyuan is a county-level city in eastern China's Shandong province, known for its rich gold mining industry and economic development.
-
B.
Xinzhuang
Xinzhuang is a major suburban town and transportation hub in Shanghai, China, known for its busy commercial areas and key metro and rail connections.
-
C.
Luzhi
Luzhi is an ancient canal town near Suzhou in China, renowned for its well-preserved waterways, stone bridges, and traditional Jiangnan architecture.
-
D.
Zhizhong
chosen
Zhizhong is a Chinese given name shared by various individuals, including historical and contemporary figures.
-
E.
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.
- 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_69ca84d1d5f88190ab878a1021ecff68 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdeca0dc508190916f2a1bbb288192 |
completed | April 2, 2026, 4:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d65296ee98819096de701e3b945001 |
completed | April 8, 2026, 1:05 p.m. |
Created at: March 30, 2026, 9:11 p.m.