Triple
T9424621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Purple Rain |
E227235
|
entity |
| Predicate | filmRunningTime |
P36872
|
FINISHED |
| Object | approximately 111 minutes |
—
|
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: approximately 111 minutes | Statement: [Purple Rain, filmRunningTime, approximately 111 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmRunningTime Context triple: [Purple Rain, filmRunningTime, approximately 111 minutes]
-
A.
filmRuntimeMinutes
Indicates the duration of a film expressed in minutes.
-
B.
filmRuntimeApprox
chosen
Indicates an approximate or estimated duration of a film, rather than its exact runtime.
-
C.
filmLength
Indicates the duration or running time of a film, typically measured in units such as minutes.
-
D.
featureLengthFilm
Indicates that the subject is a film whose running time meets or exceeds the standard length considered to be a feature film.
-
E.
hasRunningTimeCategory
Indicates that an entity is associated with a specific category based on its running time or duration.
- 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_69ca8436ba308190903e470776d2d893 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd7c8f59dc8190854dfc0d287731c6 |
completed | April 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:49 p.m.