Triple
T20418801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Centerfold |
E500788
|
entity |
| Predicate | imageStyle |
P140071
|
FINISHED |
| Object | glamorous |
—
|
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: glamorous | Statement: [Centerfold, imageStyle, glamorous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageStyle Context triple: [Centerfold, imageStyle, glamorous]
-
A.
imageOf
Indicates that one entity is a visual representation or depiction of another entity.
-
B.
videoStyle
Indicates the stylistic characteristics or presentation format applied to a video (such as tone, visual approach, or editing style).
-
C.
stylingTool
Indicates a tool or instrument used to style, shape, or arrange something (typically hair, clothing, or design elements).
-
D.
featuresStyle
Indicates that one entity exhibits, incorporates, or is characterized by a particular style associated with another entity.
-
E.
styleFor
Indicates a relationship where one entity defines, specifies, or is used as the style or styling configuration applied to 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a4686a48190a808c86aa916ad56 |
completed | April 20, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69e5766df0008190a73c4f613c29678f |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:30 a.m.