Triple
T34192146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Allegiance |
E877137
|
entity |
| Predicate | hasFilmCapture |
P83514
|
FINISHED |
| Object | Allegiance (2016 pro-shot film) |
—
|
NE NERFINISHED |
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: Allegiance (2016 pro-shot film) | Statement: [Allegiance, hasFilmCapture, Allegiance (2016 pro-shot film)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFilmCapture Context triple: [Allegiance, hasFilmCapture, Allegiance (2016 pro-shot film)]
-
A.
hasVideoRecordingAvailableOn
Indicates that a video recording of something is accessible or hosted on a specified platform, service, or medium.
-
B.
hasVideoRecording
chosen
Indicates that there exists an associated video recording capturing or documenting the referenced entity or event.
-
C.
hasCamera
Indicates that an entity is equipped with or possesses a camera.
-
D.
hasPhotogenicFeature
Indicates that an entity possesses a visual characteristic or attribute that is especially attractive or appealing when photographed.
-
E.
hasVideoInput
Indicates that an entity is equipped with or supports a video input connection or capability.
- 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ff63e6b61081909c648bf0ff279481 |
completed | May 9, 2026, 4:42 p.m. |
| PD | Predicate disambiguation | batch_69ff6381867881908ae0545df4b71df5 |
completed | May 9, 2026, 4:40 p.m. |
Created at: May 1, 2026, 1:55 a.m.