Triple
T9501284
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xi Zhongxun |
E229145
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | Qi Xin |
E206507
|
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: Qi Xin | Statement: [Xi Zhongxun, spouse, Qi Xin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Qi Xin Context triple: [Xi Zhongxun, spouse, Qi Xin]
-
A.
Qi Xin
chosen
Qi Xin is a Chinese revolutionary and former Party official best known as the mother of China’s paramount leader Xi Jinping.
-
B.
Yan Xiu
Yan Xiu was a prominent early 20th-century Chinese educator and reformer who played a key role in modernizing China's education system.
-
C.
Yongming Yanshou
Yongming Yanshou was a 10th-century Chinese Buddhist monk renowned for integrating Chan (Zen) and Pure Land practices, profoundly shaping East Asian Pure Land thought.
-
D.
Meng Haoran
Meng Haoran was a renowned High Tang poet celebrated for his tranquil landscape and nature-themed verse that deeply influenced classical Chinese poetry.
-
E.
Tao Qian
Tao Qian was a late Eastern Han dynasty warlord and governor of Xu Province, best known for ceding his territory to Liu Bei before his death.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983d4b708190a4dfef1246986a26 |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d13a0a5ec881908bb1643d2bea2c9f |
completed | April 4, 2026, 4:19 p.m. |
Created at: March 30, 2026, 7:57 p.m.