Triple
T2173697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ARPES |
E48479
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | spectroscopy method |
C9628
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: spectroscopy method Context triple: [ARPES, instanceOf, spectroscopy method]
-
A.
spectroscopic approximation
A spectroscopic approximation is a simplified theoretical or computational model used to estimate spectroscopic properties (such as energy levels, transition frequencies, or intensities) by neglecting or approximating certain physical effects to make calculations tractable.
-
B.
spectroscopic parameter
A spectroscopic parameter is a quantitative value that characterizes how a system interacts with electromagnetic radiation, such as frequencies, intensities, or line shapes observed in a spectrum.
-
C.
astronomical spectrograph
An astronomical spectrograph is an instrument that disperses light from celestial objects into its component wavelengths to measure their physical properties, such as composition, temperature, velocity, and redshift.
-
D.
infrared spectrograph
An infrared spectrograph is an instrument that disperses and records infrared light from a source to measure its intensity as a function of wavelength, enabling analysis of its physical and chemical properties.
-
E.
near-infrared spectrograph
A near-infrared spectrograph is an instrument that disperses and measures light in the near-infrared wavelength range to analyze the composition, temperature, and other properties of astronomical or laboratory targets.
- F. None of above. chosen
Provenance (1 batch)
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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
Created at: March 4, 2026, 7:45 p.m.