Triple
T10807804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | geometrization conjecture |
E255013
|
entity |
| Predicate | canonicalGeometriesCount |
P52889
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [geometrization conjecture, canonicalGeometriesCount, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canonicalGeometriesCount Context triple: [geometrization conjecture, canonicalGeometriesCount, 8]
-
A.
numberOfConfigurations
chosen
Indicates the total count of distinct configurations associated with or applicable to a given entity or situation.
-
B.
geometricConfiguration
Indicates the specific spatial arrangement and relationships among parts or elements within a geometric structure.
-
C.
hasGeometry
Indicates that an entity is associated with a specific geometric representation or spatial form.
-
D.
numberOfSides
Indicates the relationship that specifies how many sides a given object or shape has.
-
E.
formationDimension
Indicates the dimensional characteristics (such as size, scale, or extent) associated with the formation of something.
- 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_69d6aa61c15c8190a1839550c56e75e1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d733b506488190921e6a1f4168dd9e |
completed | April 9, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69d6f3188f00819094ee8d65b187a333 |
completed | April 9, 2026, 12:30 a.m. |
Created at: April 8, 2026, 9:18 p.m.