Triple
T26296564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Io plasma torus |
E661433
|
entity |
| Predicate | massLoadingRate |
P160559
|
FINISHED |
| Object | approximately 1 ton per second |
—
|
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: approximately 1 ton per second | Statement: [Io plasma torus, massLoadingRate, approximately 1 ton per second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: massLoadingRate Context triple: [Io plasma torus, massLoadingRate, approximately 1 ton per second]
-
A.
massLossRate
Indicates the rate at which an object or system is losing mass over time.
-
B.
massLossDriver
Indicates the primary process or factor responsible for causing a reduction in mass of the referenced entity.
-
C.
massContribution
Indicates that an entity contributes some or all of its mass to another entity or system.
-
D.
massBalanceTrend
Indicates the direction and rate of change in the mass balance of a system (e.g., gaining, losing, or maintaining mass) over time.
-
E.
massFunction
Indicates a relationship that assigns a quantitative mass value or distribution to an entity or set of entities.
- 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_69ee812cd48c81908054068f545f0526 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f60eaea1d08190b93b85590b8c9781 |
completed | May 2, 2026, 2:48 p.m. |
| PD | Predicate disambiguation | batch_69f602d2ec748190ae95154f34c7878f |
completed | May 2, 2026, 1:57 p.m. |
| PDg | Predicate description generation | batch_69f6037bf7a081908862a8359be80cf8 |
completed | May 2, 2026, 2 p.m. |
Created at: April 26, 2026, 10:12 p.m.