Triple
T33158174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marisa Miller |
E848642
|
entity |
| Predicate | genreOfModeling |
P180569
|
FINISHED |
| Object | swimsuit modeling |
—
|
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: swimsuit modeling | Statement: [Marisa Miller, genreOfModeling, swimsuit modeling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: genreOfModeling Context triple: [Marisa Miller, genreOfModeling, swimsuit modeling]
-
A.
genreAsModel
Indicates that one entity serves as a genre-based template or stylistic model for another entity.
-
B.
modeledWith
Indicates that something is represented, simulated, or described using a particular model, method, or modeling technique.
-
C.
genreOfRecognition
Indicates the specific genre or category in which an entity (such as a work or person) is formally recognized, honored, or awarded.
-
D.
genreOfWorkDescribedIn
Indicates that a work is characterized as belonging to a particular genre as described in another resource or context.
-
E.
genreOfWorkDescribing
Indicates that a work is used to describe or characterize the genre of another work.
- 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_69f3495b02d08190bb3d366823dffc21 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: May 1, 2026, 1:28 a.m.