Triple
T8083051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhou Lingzhao |
E188663
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Zhou |
E208540
|
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: Zhou | Statement: [Zhou Lingzhao, familyName, Zhou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Zhou Context triple: [Zhou Lingzhao, familyName, Zhou]
-
A.
Zhou
chosen
Zhou is a common Chinese surname borne by many notable figures in Chinese history and politics.
-
B.
Zhu
Zhu is a common Chinese surname borne by many notable historical and contemporary figures in China.
-
C.
Wu
Wu is a common Chinese surname borne by many notable individuals across politics, academia, entertainment, and sports.
-
D.
Zeng
Zeng is a Chinese surname and given name commonly rendered in pinyin and borne by numerous historical and contemporary figures in China.
-
E.
Fa Zhou
Fa Zhou is Mulan’s elderly, honorable father and a former soldier whose injury and devotion to family drive much of the film’s emotional conflict.
- 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb415cb4688190920868317e77bbff |
completed | March 31, 2026, 3:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc93eddef48190b5f499a5b52428c8 |
completed | April 1, 2026, 3:41 a.m. |
Created at: March 30, 2026, 5:28 p.m.