Triple
T10212726
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph and the Amazing Technicolor Dreamcoat |
E242369
|
entity |
| Predicate | originalPerformanceType |
P63774
|
FINISHED |
| Object | school performance |
—
|
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: school performance | Statement: [Joseph and the Amazing Technicolor Dreamcoat, originalPerformanceType, school performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalPerformanceType Context triple: [Joseph and the Amazing Technicolor Dreamcoat, originalPerformanceType, school performance]
-
A.
originalPerformanceFor
Indicates that one entity is the original performance or execution from which another related version, recording, or representation is derived.
-
B.
typeOfPerformances
chosen
Indicates the kinds or categories of performances associated with or offered by an entity.
-
C.
performerType
Indicates the role or category of performer responsible for carrying out an action or participating in an event.
-
D.
typicalPerformance
Indicates the usual or characteristic level at which an entity performs under normal conditions.
-
E.
performanceTypeInFilm
Indicates that a particular type or category of performance is featured or occurs within a specific film.
- 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_69d381ae26c48190985abd0e25ee5d04 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d3aa23bce881909b5deac612ec22cb |
completed | April 6, 2026, 12:42 p.m. |
| PD | Predicate disambiguation | batch_69d39559e5ac8190b88eca75956b7e6a |
completed | April 6, 2026, 11:13 a.m. |
Created at: April 6, 2026, 11:03 a.m.