Triple
T24806886
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | rhombicuboctahedron |
E620678
|
entity |
| Predicate | hasUniformNotation |
P57346
|
FINISHED |
| Object | U13 |
—
|
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: U13 | Statement: [rhombicuboctahedron, hasUniformNotation, U13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUniformNotation Context triple: [rhombicuboctahedron, hasUniformNotation, U13]
-
A.
hasAlternativeNotation
chosen
Indicates that an entity can be represented or written in a different, equivalent form or notation.
-
B.
isUniform
Indicates that all elements or parts within a given set, structure, or context share the same characteristics or value.
-
C.
usesNotationFor
Indicates that one entity employs or adopts a particular notation system or symbolic representation for another entity.
-
D.
areUniform
Indicates that all elements in a given set or collection share the same value, property, or characteristic.
-
E.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 4:50 a.m.