Triple
T16492804
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Electron |
E400606
|
entity |
| Predicate | hasClassicalRadius |
P123738
|
FINISHED |
| Object | 2.817940×10^−15 m |
—
|
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: 2.817940×10^−15 m | Statement: [Electron, hasClassicalRadius, 2.817940×10^−15 m]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasClassicalRadius Context triple: [Electron, hasClassicalRadius, 2.817940×10^−15 m]
-
A.
hasRadiusType
Indicates that an entity has a radius characterized by a specific type or classification.
-
B.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
C.
isClassicOfArea
Indicates that something is recognized as a classic or exemplary work within a particular area, field, or domain.
-
D.
hasDiameterClass
Indicates that an entity is associated with a specific category or range based on the size of its diameter.
-
E.
isClassicalObjectIn
Indicates that a classical (non-quantum) object is located within or belongs to a specified region, context, or system.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e30cb648190a52cb32896c4ac5a |
completed | April 18, 2026, 7:09 a.m. |
| PD | Predicate disambiguation | batch_69e296902d6c8190884ddb612b8c5b36 |
completed | April 17, 2026, 8:22 p.m. |
| PDg | Predicate description generation | batch_69e2d7f97e548190a474691a152bd8e8 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:13 a.m.