Triple
T26115107
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taylor Vaughan |
E658802
|
entity |
| Predicate | isImageConscious |
P159966
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Taylor Vaughan, isImageConscious, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isImageConscious Context triple: [Taylor Vaughan, isImageConscious, true]
-
A.
hasImageFeature
Indicates that an entity is associated with a specific visual characteristic or attribute extracted from an image.
-
B.
visibilityInImages
Indicates how clearly or prominently an entity can be seen or detected within one or more images.
-
C.
usesImageModel
Indicates that one entity employs or relies on an image-based model (such as a computer vision or image generation model) in relation to another entity or task.
-
D.
imagedIn
Indicates that one entity appears within or is depicted in an image associated with another entity.
-
E.
containsImage
Indicates that one entity includes or embeds an image as part of its content or structure.
- 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_69ee5bc20298819099a42be042eb2349 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f60ac643108190ae81561267155791 |
completed | May 2, 2026, 2:31 p.m. |
| PD | Predicate disambiguation | batch_69f5b0021da88190bdd4cf2698c23edf |
completed | May 2, 2026, 8:04 a.m. |
| PDg | Predicate description generation | batch_69f5f6b32a8881909baa0db57b80d56a |
completed | May 2, 2026, 1:05 p.m. |
Created at: April 26, 2026, 8:04 p.m.