Triple
T789998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Li Min |
E16890
|
entity |
| Predicate | hasRelative |
P367
|
FINISHED |
| Object | He Zizhen |
E14743
|
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 Zizhen | Statement: [Li Min, hasRelative, He Zizhen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: He Zizhen Context triple: [Li Min, hasRelative, He Zizhen]
-
A.
He Zizhen
chosen
He Zizhen was a Chinese revolutionary and early Communist Party member best known as one of Mao Zedong’s wives and a participant in the Long March.
-
B.
Mao Yuanxin
Mao Yuanxin is a Chinese political figure known as Mao Zedong’s nephew who briefly held influential positions during the final years of the Cultural Revolution.
-
C.
Kun Huang
Kun Huang was a prominent Chinese physicist and crystallographer known for his influential work in solid-state physics and lattice dynamics.
-
D.
Ding Ruchang
Ding Ruchang was a late Qing dynasty Chinese naval officer best known for leading the Beiyang Fleet during the First Sino-Japanese War.
-
E.
Xiao Zisheng
Xiao Zisheng was a Chinese educator, writer, and early associate of Mao Zedong who played a significant role in introducing Western ideas and promoting modern education in early 20th-century China.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7841b0c8190859ecd247e32c6ec |
completed | March 1, 2026, 8:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a93392bc448190a7920c86727c018c |
completed | March 5, 2026, 7:41 a.m. |
Created at: March 1, 2026, 7:38 p.m.