Triple
T18265844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | METAPOST |
E437480
|
entity |
| Predicate | supports |
P516
|
FINISHED |
| Object | Bezier curves |
—
|
NE NERFINISHED |
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: Bezier curves | Statement: [METAPOST, supports, Bezier curves]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bezier curves Context triple: [METAPOST, supports, Bezier curves]
-
A.
Bezier curves
chosen
Bézier curves are mathematically defined parametric curves widely used in computer graphics and digital design to model smooth, scalable shapes and paths.
-
B.
Catmull–Rom spline
The Catmull–Rom spline is a type of interpolating spline commonly used in computer graphics and animation to create smooth curves that pass through a given set of control points.
-
C.
B-splines
B-splines are piecewise polynomial functions widely used in computer graphics and numerical analysis to create smooth, flexible curves and surfaces controlled by a set of control points.
-
D.
Curva B
Curva B is a famous end stand in Naples’ main football stadium, renowned as the passionate home of some of S.S.C. Napoli’s most fervent supporters.
-
E.
Curve
Curve is a major contemporary theatre in Leicester, England, known for its innovative productions and striking modern architecture.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ff79851481909a4bbeb14fb00647 |
completed | April 19, 2026, 4:14 p.m. |
Created at: April 10, 2026, 10:34 a.m.