Triple
T2916189
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SMARTS 1.5-meter Telescope |
E78611
|
entity |
| Predicate | hasWavelengthRange |
P38761
|
FINISHED |
| Object | optical |
—
|
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: optical | Statement: [SMARTS 1.5-meter Telescope, hasWavelengthRange, optical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWavelengthRange Context triple: [SMARTS 1.5-meter Telescope, hasWavelengthRange, optical]
-
A.
wavelengthRangeLowerBoundMicrometers
Indicates the minimum wavelength value, expressed in micrometers, that defines the lower limit of a wavelength range for the related entity or measurement.
-
B.
hasObservationWavelength
Indicates the specific wavelength at which an observation or measurement is made or recorded.
-
C.
hasSpectralChannel
chosen
Indicates that something possesses or is associated with a specific spectral channel or band within an electromagnetic spectrum.
-
D.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
-
E.
hasFocalRatioRange
Indicates that an entity is associated with a range of possible focal ratios, specifying the minimum and maximum f-number values it can have.
- 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_69ad8b0c2ad081909ff87050ae542bb9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad97fd89d88190bc7db4b39058ae3a |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9603ddd88190b8bf91bc7517cc21 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:53 p.m.