Triple
T20147430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S II |
E491339
|
entity |
| Predicate | hasCommonWavelength |
P20341
|
FINISHED |
| Object | 6716 Å |
—
|
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: 6716 Å | Statement: [S II, hasCommonWavelength, 6716 Å]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCommonWavelength Context triple: [S II, hasCommonWavelength, 6716 Å]
-
A.
hasObservationWavelength
chosen
Indicates the specific wavelength at which an observation or measurement is made or recorded.
-
B.
supportsWavelengthRange
Indicates that an entity is capable of operating over, handling, or being compatible with a specified range of wavelengths.
-
C.
hasSpectralChannel
Indicates that something possesses or is associated with a specific spectral channel or band within an electromagnetic spectrum.
-
D.
usedWavelengthRange
Indicates the range of wavelengths that were employed or applied in performing a particular process, measurement, or operation.
-
E.
approximateWavelengthRange
Indicates the range of wavelengths that approximately characterizes or bounds the phenomenon, object, or interaction in question.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679f43bc8190a1cd4768b3e87505 |
completed | April 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69e54cfd924881909b55f3e4d3e7e070 |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:33 p.m.