Triple
T3165479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wu |
E66200
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object | Wu Man |
E175097
|
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 Man | Statement: [Wu, hasNotableBearer, Wu Man]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wu Man Context triple: [Wu, hasNotableBearer, Wu Man]
-
A.
Wu Man
chosen
Wu Man is a renowned Chinese pipa virtuoso and composer known for her innovative performances and collaborations that bring traditional Chinese music to global audiences.
-
B.
Wang Jingjiu
Wang Jingjiu was a Chinese military officer best known for commanding the National Revolutionary Army’s 87th Division during the Republican era.
-
C.
Li Xiuwen
Li Xiuwen was the wife of Chinese military leader and revolutionary Ye Ting.
-
D.
Li Xiuzhen
Li Xiuzhen was the wife of prominent Chinese military leader and politician Li Zongren, who served as acting president of the Republic of China in the mid-20th century.
-
E.
Peng Xiuwen
Peng Xiuwen was a renowned Chinese conductor and arranger best known for modernizing and popularizing traditional Chinese orchestral music in the 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_69ad8585d7988190af37365331093ccd |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada6424ee48190a29891ffbbc3811d |
completed | March 8, 2026, 4:39 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235dca2848190bc2a46d6dd1c9fc7 |
completed | March 12, 2026, 3:41 a.m. |
Created at: March 8, 2026, 3:06 p.m.