Triple
T8394073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Visible Infrared Imaging Radiometer Suite |
E198009
|
entity |
| Predicate | swathWidth |
P81986
|
FINISHED |
| Object | approximately 3000 kilometers |
—
|
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 3000 kilometers | Statement: [Visible Infrared Imaging Radiometer Suite, swathWidth, approximately 3000 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: swathWidth Context triple: [Visible Infrared Imaging Radiometer Suite, swathWidth, approximately 3000 kilometers]
-
A.
swathWidthRange
Indicates the range of possible widths covered or affected in a single pass or sweep of an action or process.
-
B.
trackWidth
Indicates the lateral distance between two parallel tracks or wheels, typically measured from center to center.
-
C.
runwayWidth
Indicates the measured width of a runway as a spatial dimension.
-
D.
executionWidth
Indicates the degree of parallelism or number of concurrent units used when executing an operation or process.
-
E.
maximumChannelWidth
Indicates the greatest allowable or observed width of a channel in the given context.
- 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_69ca82f816bc8190ab321c07d72208c1 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb8185ef60819085cfa7491d35834a |
completed | March 31, 2026, 8:10 a.m. |
| PD | Predicate disambiguation | batch_69cb70d24b248190a326aa6804f942b5 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb77690720819099de1e22b84a9563 |
completed | March 31, 2026, 7:27 a.m. |
Created at: March 30, 2026, 6:03 p.m.