Triple
T8144045
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kepler–Poinsot polyhedra |
E190163
|
entity |
| Predicate | areModeledIn |
P68217
|
FINISHED |
| Object | mathematical visualization and art |
—
|
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: mathematical visualization and art | Statement: [Kepler–Poinsot polyhedra, areModeledIn, mathematical visualization and art]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areModeledIn Context triple: [Kepler–Poinsot polyhedra, areModeledIn, mathematical visualization and art]
-
A.
modeledBy
chosen
Indicates that one entity serves as a model or representation of another, typically capturing its structure, behavior, or properties.
-
B.
basedInFilm
Indicates that something (such as a character, event, or work) is situated, set, or primarily located within the context or universe of a particular film.
-
C.
appearsIn
Indicates that an entity is present, featured, or occurs within a particular context, work, or medium.
-
D.
appearsInAdaptationBy
Indicates that an entity is featured or present in an adaptation created by a specified adapter (e.g., author, director, or studio).
-
E.
includedInFilm
Indicates that one entity (such as a scene, segment, or element) is contained within or forms part of a particular film.
- 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_69ca82bd9900819099477cdc2eb4244f |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4444bb248190beaaa2ce4b8f3eaa |
completed | March 31, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69cb369c0d0481908762c488d7f77e74 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:36 p.m.