Triple
T11081709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhang Zhidong |
E262010
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Zhidong
Zhidong is the given name of Zhang Zhidong, a prominent late Qing dynasty Chinese official and reformer.
|
E903782
|
NE FINISHED |
How this triple was built (4 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.
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.
-
B.
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.
-
C.
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.
-
D.
Shengzhi
Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
-
E.
Jianzhong
Jianzhong was a brief imperial era name used during the reign of Emperor Dezong in the Tang dynasty, marking a specific period in his rule.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Zhidong Triple: [Zhang Zhidong, givenName, Zhidong]
Generated description
Zhidong is the given name of Zhang Zhidong, a prominent late Qing dynasty Chinese official and reformer.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Zhidong Target entity description: Zhidong is the given name of Zhang Zhidong, a prominent late Qing dynasty Chinese official and reformer.
-
A.
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.
-
B.
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.
-
C.
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.
-
D.
Shengzhi
Shengzhi is the given name of Tang Shengzhi, a prominent Chinese Nationalist general active during the early 20th century.
-
E.
Jianzhong
Jianzhong was a brief imperial era name used during the reign of Emperor Dezong in the Tang dynasty, marking a specific period in his rule.
- F. None of above. chosen
Provenance (5 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_69d6aa9983c08190b0ef61603b69feac |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d799985650819089b2c0f35a212414 |
completed | April 9, 2026, 12:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e3e789d7248190a40de0bdda539f45 |
completed | April 18, 2026, 8:20 p.m. |
| NEDg | Description generation | batch_69e3f2c889dc81909a04c1db0509e3d9 |
completed | April 18, 2026, 9:08 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69e3f4746dbc8190a0e28202ad5e6b4f |
completed | April 18, 2026, 9:15 p.m. |
Created at: April 8, 2026, 9:27 p.m.