Triple
T14102803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Friday film series |
E339423
|
entity |
| Predicate | typicalRuntimePerFilm |
P36872
|
FINISHED |
| Object | approximately 90 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 90 minutes | Statement: [Friday film series, typicalRuntimePerFilm, approximately 90 minutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRuntimePerFilm Context triple: [Friday film series, typicalRuntimePerFilm, approximately 90 minutes]
-
A.
filmRuntimeApprox
chosen
Indicates an approximate or estimated duration of a film, rather than its exact runtime.
-
B.
typicalRuntimePerShort
Indicates the usual or average amount of time it takes to complete a short instance of the referenced activity or process.
-
C.
typicalRuntimeRange
Indicates the usual lower and upper bounds of time typically required for an entity to run or complete its operation.
-
D.
filmRuntimeMinutes
Indicates the duration of a film expressed in minutes.
-
E.
filmLength
Indicates the duration or running time of a film, typically measured in units such as minutes.
- 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_69d81c69b5c8819094aa1abf18302908 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de5fbbf0b08190ba1ea3657d6db005 |
completed | April 14, 2026, 3:39 p.m. |
| PD | Predicate disambiguation | batch_69de05b2f7e481908a9a7d40153234c0 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:22 p.m.