Triple
T17752465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SU(2) |
E443145
|
entity |
| Predicate | hasHaarMeasure |
P128197
|
FINISHED |
| Object | finite |
—
|
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: finite | Statement: [SU(2), hasHaarMeasure, finite]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHaarMeasure Context triple: [SU(2), hasHaarMeasure, finite]
-
A.
hasLebesgueMeasure
Indicates that a set is assigned a specific value by the Lebesgue measure, representing its "size" in the sense of measure theory.
-
B.
hasNonMeasurableSets
Indicates that within a given set or space, there exist subsets that are not measurable under the specified measure or sigma-algebra.
-
C.
hasHausdorffDimension
Indicates that a mathematical object is associated with a specific Hausdorff dimension value, expressing the fractal or geometric complexity of the object.
-
D.
measurability
Indicates that a quantity, property, or outcome can be defined, quantified, or assessed using a consistent measurement framework.
-
E.
spectralMeasure
Indicates a relationship where a measure assigns values to sets in a spectrum, typically capturing how a quantity (like probability or mass) is distributed across spectral components.
- F. None of above. chosen
Provenance (4 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_69d8b9edf16c8190a59ebd245d378f4f |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4841b3ccc8190b3241b3e0fa4b2e8 |
completed | April 19, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3cfab7edc8190b663282d565a0389 |
completed | April 18, 2026, 6:38 p.m. |
Created at: April 10, 2026, 10:10 a.m.