Triple
T24811017
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mueller calculus |
E620786
|
entity |
| Predicate | transformationLaw |
P154777
|
FINISHED |
| Object | S_out = M · S_in |
—
|
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: S_out = M · S_in | Statement: [Mueller calculus, transformationLaw, S_out = M · S_in]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: transformationLaw Context triple: [Mueller calculus, transformationLaw, S_out = M · S_in]
-
A.
convertsLaw
Indicates that one entity transforms or translates a law from one form, system, or representation into another.
-
B.
hasTransformationFormula
chosen
Indicates that there exists a specific formula or rule that defines how one entity is transformed into another.
-
C.
usesTransformation
Indicates that one entity applies or relies on a specific transformation process, method, or function to operate on or convert another entity.
-
D.
transformationRelation
Indicates a relationship where one entity is changed, converted, or transformed into another entity or state.
-
E.
settingOfTransformation
Indicates the place, context, or environment in which a transformation of an entity or state occurs.
- 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f5ffc74fa481909b4fe24a9337f9eb |
completed | May 2, 2026, 1:44 p.m. |
| PD | Predicate disambiguation | batch_69f5f7f99dc08190afcfb3bc4dfbec1d |
completed | May 2, 2026, 1:11 p.m. |
Created at: April 18, 2026, 4:50 a.m.