Triple
T13331105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Wu |
E317573
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wu |
E66200
|
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: Wu | Statement: [Daniel Wu, familyName, Wu]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wu Context triple: [Daniel Wu, familyName, Wu]
-
A.
Wu
chosen
Wu is a common Chinese surname borne by many notable individuals across politics, academia, entertainment, and sports.
-
B.
Zhu
Zhu is a common Chinese surname borne by many notable historical and contemporary figures in China.
-
C.
Zhou
Zhou is a common Chinese surname borne by many notable figures in Chinese history and politics.
-
D.
Wu Yi
Wu Yi is a Chinese politician who served as Vice Premier of the State Council and was widely known for her leadership in economic policy and public health crises such as the SARS outbreak.
-
E.
Wu Xiang
Wu Xiang was a Ming dynasty military official and nobleman best known as the father of the powerful general and later Qing collaborator Wu Sangui.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992fffa0819086610ae3bed2e2f9 |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f730641f588190886119506e6dde8f |
completed | May 3, 2026, 11:24 a.m. |
Created at: April 9, 2026, 9:30 p.m.