Triple
T35709316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pantomimes lumineuses |
E1031808
|
entity |
| Predicate | runningTimeOfIndividualFilms |
P36872
|
FINISHED |
| Object | approximately 10 to 15 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 10 to 15 minutes | Statement: [Pantomimes lumineuses, runningTimeOfIndividualFilms, approximately 10 to 15 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: runningTimeOfIndividualFilms Context triple: [Pantomimes lumineuses, runningTimeOfIndividualFilms, approximately 10 to 15 minutes]
-
A.
filmRuntimeApprox
chosen
Indicates an approximate or estimated duration of a film, rather than its exact runtime.
-
B.
filmRuntimeMinutes
Indicates the duration of a film expressed in minutes.
-
C.
timePeriodOfFilm
Indicates the historical or fictional time period in which the events of the film are set.
-
D.
filmLength
Indicates the duration or running time of a film, typically measured in units such as minutes.
-
E.
filmLengthSpecialization
Indicates a relationship where one entity specifies or refines the particular length or duration characteristics of a film defined by another entity.
- 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_69f76e0df1d08190965b1c6dff94c391 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7a34f8ee08190a040304635539a8f |
completed | May 3, 2026, 7:34 p.m. |
| PD | Predicate disambiguation | batch_69f7a06f125c8190843af194f042a465 |
completed | May 3, 2026, 7:22 p.m. |
Created at: May 3, 2026, 4:05 p.m.