Triple
T19245069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Educational Pictures |
E481228
|
entity |
| Predicate | filmLengthSpecialization |
P135040
|
FINISHED |
| Object | shorts |
—
|
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: shorts | Statement: [Educational Pictures, filmLengthSpecialization, shorts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: filmLengthSpecialization Context triple: [Educational Pictures, filmLengthSpecialization, shorts]
-
A.
filmLength
Indicates the duration or running time of a film, typically measured in units such as minutes.
-
B.
featureLengthFilm
Indicates that the subject is a film whose running time meets or exceeds the standard length considered to be a feature film.
-
C.
filmLengthFocus
Indicates that the relationship or action centers on the duration or running time of a film.
-
D.
filmRuntimeMinutes
Indicates the duration of a film expressed in minutes.
-
E.
filmRuntimeApprox
Indicates an approximate or estimated duration of a film, rather than its exact runtime.
- F. None of above. chosen
Provenance (4 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_69d8e8cd9d1081908a181d02b88b59b8 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5faf47820819081e8b6af852bb1dd |
completed | April 20, 2026, 10:07 a.m. |
| PD | Predicate disambiguation | batch_69e4dd002d00819088b625056edfb74e |
completed | April 19, 2026, 1:47 p.m. |
| PDg | Predicate description generation | batch_69e4ddcf50108190a09d0f1291c17374 |
completed | April 19, 2026, 1:51 p.m. |
Created at: April 10, 2026, 1:27 p.m.