Triple
T25063709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Levi-Civita field |
E627727
|
entity |
| Predicate | hasAnalyticUse |
P116683
|
FINISHED |
| Object | definition of derivatives via infinitesimal quotients |
—
|
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: definition of derivatives via infinitesimal quotients | Statement: [Levi-Civita field, hasAnalyticUse, definition of derivatives via infinitesimal quotients]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAnalyticUse Context triple: [Levi-Civita field, hasAnalyticUse, definition of derivatives via infinitesimal quotients]
-
A.
isAnalyticOn
Indicates that a function is analytic (holomorphic) throughout a specified domain or region.
-
B.
hasAnalysis
Indicates that an entity is associated with, or has undergone, a particular analysis or examination.
-
C.
hasAnalyticGrammar
Indicates that an entity possesses or is characterized by an analytic grammar, where grammatical relationships are expressed primarily through separate words rather than inflection.
-
D.
hasAnalysisType
chosen
Indicates that one entity is associated with, or characterized by, a specific type or category of analysis applied to it.
-
E.
usedDataAnalytics
Indicates that an entity applied data analytics techniques or insights in performing an action or making a decision related to another entity.
- 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_69e2ff2d71dc8190b4758e57d643cbe4 |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 6:10 a.m.