Triple
T26629518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Multi Unit Spectroscopic Explorer |
E668453
|
entity |
| Predicate | spatialSampling |
P68593
|
FINISHED |
| Object | 0.2 arcseconds per spatial pixel |
—
|
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: 0.2 arcseconds per spatial pixel | Statement: [Multi Unit Spectroscopic Explorer, spatialSampling, 0.2 arcseconds per spatial pixel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spatialSampling Context triple: [Multi Unit Spectroscopic Explorer, spatialSampling, 0.2 arcseconds per spatial pixel]
-
A.
hasSpatialResolution
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
-
B.
samplingType
Indicates the method or strategy used to select samples from a larger set or population.
-
C.
timeSampling
Indicates that one entity specifies how or at what intervals another entity is sampled or measured over time.
-
D.
spatialCorrelation
Indicates a relationship where two spatial variables or patterns vary together in a statistically related way across space.
-
E.
samplingResolution
chosen
Indicates the level of detail or granularity at which data is sampled or measurements are taken in a process or system.
- F. None of above.
Provenance (3 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_69ee9cff507c819092b95bf7219a702e |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f61a17a7788190946f7e32d63cd43f |
completed | May 2, 2026, 3:36 p.m. |
| PD | Predicate disambiguation | batch_69f611ab768c8190b1849c15a3e59dda |
completed | May 2, 2026, 3 p.m. |
Created at: April 27, 2026, 2:24 a.m.