Triple
T24600785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hausdorff measure |
E608815
|
entity |
| Predicate | isOuterMeasure |
P156709
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Hausdorff measure, isOuterMeasure, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOuterMeasure Context triple: [Hausdorff measure, isOuterMeasure, true]
-
A.
isOuterRegularOnBorelSets
Indicates that a measure is outer regular when restricted to Borel sets, meaning each Borel set’s measure equals the infimum of the measures of open sets containing it.
-
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.
hasLebesgueMeasure
Indicates that a set is assigned a specific value by the Lebesgue measure, representing its "size" in the sense of measure theory.
-
D.
impliesUnderMeasurability
Indicates that one property or condition guarantees that another property or condition is measurable (in the measure-theoretic sense).
-
E.
measurability
Indicates that a quantity, property, or outcome can be defined, quantified, or assessed using a consistent measurement framework.
- 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_69e2c4cf54248190af7b0c2d9ade9830 |
completed | April 17, 2026, 11:39 p.m. |
| NER | Named-entity recognition | batch_69f2be044d4c819094e14eda28d371a7 |
completed | April 30, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f2a6ca751c8190a040c10d701ecf3a |
completed | April 30, 2026, 12:48 a.m. |
| PDg | Predicate description generation | batch_69f2b8b8bc5881908df49c0b07110246 |
completed | April 30, 2026, 2:04 a.m. |
Created at: April 18, 2026, 2:30 a.m.