Triple
T985197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love, Antosha |
E21262
|
entity |
| Predicate | usesFootageType |
P22752
|
FINISHED |
| Object | archival footage |
—
|
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: archival footage | Statement: [Love, Antosha, usesFootageType, archival footage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesFootageType Context triple: [Love, Antosha, usesFootageType, archival footage]
-
A.
usesInstantReplay
Indicates that an entity employs instant replay technology or review during an event, action, or decision process.
-
B.
hasMusicVideo
Indicates that a piece of media (typically a song) is associated with or accompanied by a music video.
-
C.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
-
D.
hasFilmColorType
Indicates that a film is associated with a particular color process or color classification (e.g., color, black-and-white).
-
E.
usesImageryOf
Indicates that one entity employs or incorporates visual or sensory imagery that depicts, references, or symbolically represents another entity.
- 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_69a493c383dc8190a03257f22d4b4183 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4959fe48190a78bd811cbc888ab |
completed | March 1, 2026, 9:50 p.m. |
| PD | Predicate disambiguation | batch_69a4b2abccbc8190a83af432f89eacf5 |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b38630848190bd3898a4f42018ad |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.