Triple
T12373110
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stratonovich integral |
E295051
|
entity |
| Predicate | definitionInvolves |
P104836
|
FINISHED |
| Object | midpoint Riemann sums |
—
|
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: midpoint Riemann sums | Statement: [Stratonovich integral, definitionInvolves, midpoint Riemann sums]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definitionInvolves Context triple: [Stratonovich integral, definitionInvolves, midpoint Riemann sums]
-
A.
definitionText
Indicates the textual content that provides the definition or explanatory meaning of a concept, term, or entity.
-
B.
oftenDefines
Indicates that one entity frequently serves to specify, characterize, or determine the nature, meaning, or boundaries of another entity.
-
C.
defined
Indicates that one entity specifies, explains, or establishes the meaning, scope, or identity of another entity.
-
D.
definitionOfRelatedConcept
Indicates that one concept provides the formal meaning, explanation, or characterization of another closely related concept.
-
E.
secondDefinition
Indicates that one entity serves as an alternative or secondary definition or meaning for another entity.
- 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_69d6ab6d8a4081908636601e69ddf262 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d942a2d6e08190a13c7ff89af09354 |
completed | April 10, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69d93ecf6b548190a394b6b56a0c1c68 |
completed | April 10, 2026, 6:17 p.m. |
| PDg | Predicate description generation | batch_69d9429ff2bc8190b09adf8f57fad451 |
completed | April 10, 2026, 6:34 p.m. |
Created at: April 8, 2026, 9:54 p.m.