Triple
T4485844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faraday constant |
E107235
|
entity |
| Predicate | hasSymbolInEquations |
P29171
|
FINISHED |
| Object | F |
—
|
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: F | Statement: [Faraday constant, hasSymbolInEquations, F]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSymbolInEquations Context triple: [Faraday constant, hasSymbolInEquations, F]
-
A.
hasSymbolicForm
chosen
Indicates that one entity serves as the symbolic representation or abstract form of another entity.
-
B.
hasEquationSide
Indicates a relationship where a particular expression or term belongs to a specific side (e.g., left or right) of an equation.
-
C.
supportsEquations
Indicates that one entity provides the capability to handle, display, or work with mathematical equations for another entity or within a given context.
-
D.
hasVarianceSymbol
Indicates that one entity is associated with, or represented by, a specific variance symbol in a mathematical or statistical context.
-
E.
hasNonLogicalSymbol
Indicates that a given formal system, expression, or language includes at least one symbol that is not part of its logical vocabulary (e.g., not a connective, quantifier, or equality sign).
- 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_69bd43f84f788190a1383579c4a595be |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd556d29f08190bab1e872dd7e819f |
completed | March 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69bd5213e3d0819094b026989e686f01 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 12:59 p.m.