Triple
T5725887
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Europa |
E126262
|
entity |
| Predicate | magneticInteraction |
P66109
|
FINISHED |
| Object | induces magnetic field in Jupiter’s magnetosphere |
—
|
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: induces magnetic field in Jupiter’s magnetosphere | Statement: [Europa, magneticInteraction, induces magnetic field in Jupiter’s magnetosphere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: magneticInteraction Context triple: [Europa, magneticInteraction, induces magnetic field in Jupiter’s magnetosphere]
-
A.
magneticField
Indicates the presence, strength, or configuration of a magnetic field associated with an entity or region.
-
B.
hasMagneticMoment
Indicates that an entity possesses a magnetic moment, characterizing the strength and orientation of its magnetism.
-
C.
magneticFieldStrength
Indicates the intensity or magnitude of a magnetic field associated with an entity or at a specific location.
-
D.
magneticFieldCharacteristic
Indicates a relationship where a magnetic field is associated with or exhibits a specific characteristic or property.
-
E.
usesMagnetType
Indicates that one entity employs or operates with a specific type of magnet in its function or configuration.
- 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_69c0082f723881908ce8bb13a0c0f8b7 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c029014588819094a2a0f6f9b66bab |
completed | March 22, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c021c6488881909bed4a4534d57f70 |
completed | March 22, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69c028fec2bc819083f5dca6a8d9d435 |
completed | March 22, 2026, 5:38 p.m. |
Created at: March 22, 2026, 3:47 p.m.