Triple
T6327940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fermat’s principle of least time |
E141903
|
entity |
| Predicate | didNotOriginallyUse |
P46750
|
FINISHED |
| Object | calculus of variations formalism |
—
|
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: calculus of variations formalism | Statement: [Fermat’s principle of least time, didNotOriginallyUse, calculus of variations formalism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: didNotOriginallyUse Context triple: [Fermat’s principle of least time, didNotOriginallyUse, calculus of variations formalism]
-
A.
originallyHad
Indicates that an entity previously possessed, contained, or was associated with something before a change, loss, or transformation occurred.
-
B.
doesNotUse
Indicates that one entity intentionally refrains from employing, utilizing, or relying on another entity, method, or resource.
-
C.
didNotBecome
Indicates that an expected or potential change of state, role, or condition between entities did not occur.
-
D.
notInOriginalStageVersion
chosen
Indicates that the referenced element does not appear in the original stage version of the work or production.
-
E.
didNotExplicitlyUseTerm
Indicates that an entity performed an action or produced content without directly or specifically using a particular term.
- 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_69c008d201748190917e69c41ba3f978 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c064e9532081908277f10ec380a486 |
completed | March 22, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69c060e7e2d48190af9d004236466788 |
completed | March 22, 2026, 9:36 p.m. |
Created at: March 22, 2026, 4:29 p.m.