Triple
T16150949
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dirac operator |
E391906
|
entity |
| Predicate | symbolIs |
P121608
|
FINISHED |
| Object | Clifford multiplication by cotangent vectors |
—
|
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: Clifford multiplication by cotangent vectors | Statement: [Dirac operator, symbolIs, Clifford multiplication by cotangent vectors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolIs Context triple: [Dirac operator, symbolIs, Clifford multiplication by cotangent vectors]
-
A.
symbolType
Indicates the classification or category of a symbol based on its role, form, or function within a given system.
-
B.
symbolElement
Indicates that one entity is a constituent element or component that makes up the other entity, which is treated as a symbol.
-
C.
symbolText
Indicates that a symbol is associated with or represented by a specific piece of text.
-
D.
symbolLinked
Indicates a relationship where one symbol is connected or associated with another symbol, typically to show reference, correspondence, or linkage between them.
-
E.
symbolVariant
Indicates that one symbol is an alternative graphical or stylistic form of another symbol.
- 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_69d87f1c65e48190aa2b4c472e9bafc4 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21d9724808190a8332987583a345a |
completed | April 17, 2026, 11:46 a.m. |
| PD | Predicate disambiguation | batch_69e1828abb608190a99d86bce1d77de2 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e18445155481909892b8aaa23cc159 |
completed | April 17, 2026, 12:52 a.m. |
Created at: April 10, 2026, 5:01 a.m.