Triple
T35561049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UVOT |
E1027635
|
entity |
| Predicate | hasPhotometricFilters |
P62581
|
FINISHED |
| Object | ultraviolet filters |
—
|
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: ultraviolet filters | Statement: [UVOT, hasPhotometricFilters, ultraviolet filters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhotometricFilters Context triple: [UVOT, hasPhotometricFilters, ultraviolet filters]
-
A.
hasPhotometry
Indicates that an entity possesses or is associated with photometric data or measurements.
-
B.
usesPhotometryFrom
Indicates that one entity bases its measurements, analyses, or results on photometric data obtained from another entity.
-
C.
hasFilterWheel
Indicates that an entity is equipped with or connected to a filter wheel component used to select among multiple filters.
-
D.
hasSpectralChannel
Indicates that something possesses or is associated with a specific spectral channel or band within an electromagnetic spectrum.
-
E.
photometricSystem
chosen
Indicates the photometric measurement system or filter set used when observing or recording a quantity.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fb6fdc7eb081908ab8475efb38c430 |
completed | May 6, 2026, 4:44 p.m. |
| PD | Predicate disambiguation | batch_69fb5a986e588190b7a10892bd2ff44c |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:04 p.m.