Triple
T12417367
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ohm's law for AC |
E296670
|
entity |
| Predicate | relatesToQuantity |
P105005
|
FINISHED |
| Object | rms voltage |
—
|
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: rms voltage | Statement: [Ohm's law for AC, relatesToQuantity, rms voltage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatesToQuantity Context triple: [Ohm's law for AC, relatesToQuantity, rms voltage]
-
A.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
B.
concernsQuantity
Indicates that the relationship or statement specifically pertains to the amount, number, or measurable extent of something.
-
C.
mainQuantity
Indicates that the associated value represents the primary or principal quantity in a given context or relationship.
-
D.
belongsToQuantityKind
Indicates that something is associated with, or classified under, a particular kind or category of quantity (such as length, mass, or time).
-
E.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
- 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_69d6ada0640c81908c061d7fb3d47786 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e1888b48190bd750f839a26e99e |
completed | April 10, 2026, 7:23 p.m. |
| PD | Predicate disambiguation | batch_69d94d354b488190adc83fb4f2770dd5 |
completed | April 10, 2026, 7:19 p.m. |
| PDg | Predicate description generation | batch_69d94e15f21c8190831c9562ffdd4fda |
completed | April 10, 2026, 7:23 p.m. |
Created at: April 8, 2026, 9:55 p.m.