Triple
T16614862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peano curve |
E403670
|
entity |
| Predicate | topologicalDimensionOfImage |
P53031
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Peano curve, topologicalDimensionOfImage, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topologicalDimensionOfImage Context triple: [Peano curve, topologicalDimensionOfImage, 2]
-
A.
dimensionCount
Indicates the number of distinct dimensions or axes associated with an entity or data structure.
-
B.
graphicsDimension
Indicates a relationship where an entity has or is associated with a specific graphical size or dimensional properties.
-
C.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
-
D.
hasDimensionality
chosen
Indicates that an entity possesses a specific number of dimensions or a particular dimensional structure.
-
E.
imageChannels
Indicates the number and types of color or data channels present in an image (e.g., RGB, RGBA, grayscale).
- 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_69d883897eb481909eaaa088ba9918d9 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3609935a88190baa56f3a42b2ecd1 |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
Created at: April 10, 2026, 5:17 a.m.