Triple
T24811031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mueller calculus |
E620786
|
entity |
| Predicate | classificationOfSystems |
P6736
|
FINISHED |
| Object | nondepolarizing Mueller matrices |
—
|
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: nondepolarizing Mueller matrices | Statement: [Mueller calculus, classificationOfSystems, nondepolarizing Mueller matrices]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: classificationOfSystems Context triple: [Mueller calculus, classificationOfSystems, nondepolarizing Mueller matrices]
-
A.
classificationSystem
chosen
Indicates a relationship where an entity is organized or categorized according to a particular classification scheme or taxonomy.
-
B.
classificationSystemBasedOn
Indicates that one classification system is organized, defined, or derived using another classification system as its basis or reference framework.
-
C.
classificationSystemName
Indicates the name or label assigned to a particular classification system used to categorize or organize entities.
-
D.
definesClassification
Indicates that one entity specifies or establishes the classification or category to which another entity belongs.
-
E.
modelsSystemsWith
Indicates that one entity creates or uses a representation or abstraction to describe, analyze, or simulate another system.
- 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_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 4:50 a.m.