Triple
T1463130
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gauss's law for magnetism |
E31558
|
entity |
| Predicate | quantityDescribed |
P9758
|
FINISHED |
| Object | magnetic flux |
—
|
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: magnetic flux | Statement: [Gauss's law for magnetism, quantityDescribed, magnetic flux]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: quantityDescribed Context triple: [Gauss's law for magnetism, quantityDescribed, magnetic flux]
-
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.
quantityType
chosen
Indicates that one entity is the type or category of quantity to which another entity (a specific measured or measurable amount) belongs.
-
C.
numberOfUnits
Indicates the quantity or count of discrete units associated with an entity or relationship.
-
D.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
-
E.
quantifies
Indicates that one entity expresses or specifies the amount, number, or degree of another entity.
- 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_69a49917dfc081909acdbdf5d684f1ef |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c5b89708819084fb9ba4ff293b8b |
completed | March 1, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69a4c48121e48190946c23c583e5fb64 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8 p.m.