Triple
T25725586
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Itô–Taylor expansion |
E645107
|
entity |
| Predicate | accuracyCharacterization |
P159023
|
FINISHED |
| Object | strong order of convergence |
—
|
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: strong order of convergence | Statement: [Itô–Taylor expansion, accuracyCharacterization, strong order of convergence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: accuracyCharacterization Context triple: [Itô–Taylor expansion, accuracyCharacterization, strong order of convergence]
-
A.
scopeCharacterization
Indicates how the extent, boundaries, or coverage of something is defined, described, or qualified in relation to another entity or context.
-
B.
sourceCharacterization
Indicates that one entity describes, explains, or characterizes the origin, provenance, or source of another entity.
-
C.
resultCharacterization
Indicates how the outcome of an event, process, or action is qualitatively described or characterized.
-
D.
chargesCharacterization
Indicates how legal or formal charges against an entity are described, classified, or characterized.
-
E.
ruleCharacterization
Indicates that one rule is described, defined, or characterized in terms of another rule or set of rules.
- 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_69e77e8476fc8190bd5e9d05b89fad0a |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fcb6562481909de5461493ab10b1 |
completed | May 2, 2026, 1:31 p.m. |
| PD | Predicate disambiguation | batch_69f480824a1c81908a8a492eedbc2596 |
completed | May 1, 2026, 10:29 a.m. |
| PDg | Predicate description generation | batch_69f48b9058d081908ec9af261ee092e2 |
completed | May 1, 2026, 11:16 a.m. |
Created at: April 21, 2026, 10:23 p.m.