Triple
T6877340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ampere |
E158703
|
entity |
| Predicate | belongsToQuantityKind |
P73891
|
FINISHED |
| Object | current |
—
|
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: current | Statement: [ampere, belongsToQuantityKind, current]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToQuantityKind Context triple: [ampere, belongsToQuantityKind, current]
-
A.
belongsToPhysicalQuantity
Indicates that one entity is a component, attribute, or part of a specific physical quantity, linking it to that quantity as its owner or container.
-
B.
quantificationType
Indicates the specific kind or category of quantity or measurement being applied in a given context.
-
C.
usesQuantity
Indicates that one entity employs or applies a specified amount or measure of another entity in performing an action or fulfilling a function.
-
D.
isLocalQuantity
Indicates that a quantity is specific to a particular context, location, or subsystem rather than being globally applicable.
-
E.
hasKeyQuantity
Indicates that an entity is associated with a primary or defining quantity that characterizes or measures it.
- 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_69c68832af1481908ce356e133ebaebe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8ccc29c8190904cb73c4cbb5dca |
completed | March 27, 2026, 7:21 p.m. |
| PD | Predicate disambiguation | batch_69c6d7b363dc8190a7225b540ab2bc40 |
completed | March 27, 2026, 7:17 p.m. |
| PDg | Predicate description generation | batch_69c6d8c48ba48190b8d3aa7b8d22816b |
completed | March 27, 2026, 7:21 p.m. |
Created at: March 27, 2026, 2:22 p.m.