Triple
T15459388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liu Shaoqi |
E371856
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object | He Baozhen |
E371861
|
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: He Baozhen | Statement: [Liu Shaoqi, spouse, He Baozhen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: He Baozhen Context triple: [Liu Shaoqi, spouse, He Baozhen]
-
A.
He Baozhen
chosen
He Baozhen was the wife of Chinese revolutionary leader and former President of the People’s Republic of China Liu Shaoqi.
-
B.
Su Zhu
Su Zhu is the birth name of Hua Guofeng, the Chinese Communist leader who briefly succeeded Mao Zedong as paramount leader of China in the late 1970s.
-
C.
He Liliang
He Liliang was the wife of Chinese diplomat and former foreign minister Huang Hua.
-
D.
Jiang Baili
Jiang Baili was a prominent early 20th-century Chinese military strategist and reformer who played a key role in modernizing China's armed forces and influencing Republican-era military thought.
-
E.
Zongren
Zongren is the given name of Li Zongren, a prominent Chinese military commander and political leader of the early to mid-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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f1623f0819086f6fc2bfd536609 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b9817c819082e5c571b08bafb5 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:32 a.m.