Triple
T4485706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Faraday effect |
E107232
|
entity |
| Predicate | VerdetConstantUnits |
P9759
|
FINISHED |
| Object | radians per tesla per meter |
—
|
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: radians per tesla per meter | Statement: [Faraday effect, VerdetConstantUnits, radians per tesla per meter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: VerdetConstantUnits Context triple: [Faraday effect, VerdetConstantUnits, radians per tesla per meter]
-
A.
naturalUnitsValue
Indicates that a quantity is expressed in natural units, specifying its value when fundamental physical constants are normalized (e.g., c = ħ = k_B = 1).
-
B.
standardUnitRelation
Indicates a relationship where one unit is defined, measured, or interpreted in terms of a recognized standard unit.
-
C.
unitSystem
Indicates the system of measurement units (such as metric or imperial) that is used to quantify associated values or attributes.
-
D.
convertedUnit
Indicates that one unit is the result of converting a quantity expressed in another unit.
-
E.
SIUnit
chosen
Indicates that something is expressed or measured using a unit from the International System of Units (SI).
- 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.