Triple
T12326924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liù |
E293852
|
entity |
| Predicate | settingOfOpera |
P12690
|
FINISHED |
| Object | legendary Peking |
—
|
LITERAL 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: legendary Peking | Statement: [Liù, settingOfOpera, legendary Peking]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingOfOpera Context triple: [Liù, settingOfOpera, legendary Peking]
-
A.
operaAct
Indicates that an entity performs in or takes part in an act (segment) of an opera performance.
-
B.
associatedOpera
Indicates that there is a relationship linking an entity to an opera with which it is connected or related (e.g., as subject, inspiration, or context).
-
C.
fromOperaSetIn
Indicates that an opera originates from or is part of a narrative that is set in a particular place or setting.
-
D.
theatricalSetting
chosen
Indicates the spatial or contextual environment in which a theatrical performance or dramatic action takes place.
-
E.
operaStructureRole
Indicates the functional or narrative role that a structural element plays within an opera.
- 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_69d6ab6ae0dc8190b1522a9c1c55c114 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.