Triple
T27051398
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xun Huisheng |
E684780
|
entity |
| Predicate | collectiveNickname |
P52939
|
FINISHED |
| Object | Four Great Dan of Peking opera |
—
|
NE NERFINISHED |
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: Four Great Dan of Peking opera | Statement: [Xun Huisheng, collectiveNickname, Four Great Dan of Peking opera]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectiveNickname Context triple: [Xun Huisheng, collectiveNickname, Four Great Dan of Peking opera]
-
A.
collectivelyKnownAs
chosen
Indicates that multiple entities are referred to together under a single shared name or designation.
-
B.
notableTeamNickname
Indicates that a team is commonly known by a particular nickname that is notable or widely recognized.
-
C.
teamNicknamedAfter
Indicates that a team is commonly referred to by a nickname derived from or inspired by another entity.
-
D.
series1Nickname
Indicates that one entity is used as a nickname or informal alternative name for another entity within the context of a first series.
-
E.
mascotCollectiveName
Indicates that a mascot is associated with and represents a particular collective group, organization, or team name.
- F. None of above.
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_69ef14829fac8190914bef9ecc3005d7 |
completed | April 27, 2026, 7:47 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 8:14 a.m.