Triple
T18794269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Zhidong |
E459592
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Zhidong |
E903782
|
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: Zhidong | Statement: [Zhang Zhidong, givenName, Zhidong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhidong Context triple: [Zhang Zhidong, givenName, Zhidong]
-
A.
Zhidong
chosen
Zhidong is the given name of Zhang Zhidong, a prominent late Qing dynasty Chinese official and reformer.
-
B.
Zhu Dong
Zhu Dong was a historical Chinese scholar and educator credited with establishing the influential Yuelu Academy, one of China’s renowned ancient academies of classical learning.
-
C.
Keqiang
Keqiang is the given name of Li Keqiang, who served as the Premier of the People's Republic of China from 2013 to 2023.
-
D.
Yuanpei
Yuanpei is the given name of Cai Yuanpei, a prominent Chinese educator and reformer who served as president of Peking University in the early 20th century.
-
E.
Shengzhi
Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5a01cc0c0819098ef4326e82ff524 |
completed | April 20, 2026, 3:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a05472071b88190a74e18be8699f0c6 |
completed | May 14, 2026, 3:53 a.m. |
Created at: April 10, 2026, 11:53 a.m.