Triple
T15502496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Khinchin's constant |
E378994
|
entity |
| Predicate | measureContext |
P110189
|
FINISHED |
| Object | Lebesgue measure on the real numbers |
—
|
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: Lebesgue measure on the real numbers | Statement: [Khinchin's constant, measureContext, Lebesgue measure on the real numbers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: measureContext Context triple: [Khinchin's constant, measureContext, Lebesgue measure on the real numbers]
-
A.
measurement
Indicates a relationship where one entity quantifies or assigns a value to some property, attribute, or extent of another entity according to a defined scale or standard.
-
B.
measureType
Indicates the specific kind or category of measurement that characterizes how a quantity or value is assessed.
-
C.
measureOf
Indicates that one entity serves as a quantitative or qualitative assessment or metric describing a property, extent, or magnitude of another entity.
-
D.
measurementSetting
chosen
Indicates the specific conditions, parameters, or configuration under which a measurement is taken or recorded.
-
E.
measured
Indicates that one entity has determined or quantified a property, amount, or extent of another entity using some standard or instrument.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fcc5bb88190b8a9a81419a9a38b |
completed | April 16, 2026, 1:47 a.m. |
| PD | Predicate disambiguation | batch_69ded2896a9c8190a8b9627deb3c17b4 |
completed | April 14, 2026, 11:49 p.m. |
Created at: April 10, 2026, 3:54 a.m.