Triple
T1180318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GPON |
E25120
|
entity |
| Predicate | downstreamWavelength |
P5242
|
FINISHED |
| Object | 1490 nm |
—
|
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: 1490 nm | Statement: [GPON, downstreamWavelength, 1490 nm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: downstreamWavelength Context triple: [GPON, downstreamWavelength, 1490 nm]
-
A.
downstreamFrom
Indicates that one entity is located or occurs at a point further along the natural flow or direction of another entity, typically in a linear or directional system such as a river, pipeline, or process sequence.
-
B.
primaryWavelength
chosen
Indicates the main or dominant wavelength associated with an entity, such as the principal wavelength at which it emits, reflects, or operates.
-
C.
hasObservationWavelength
Indicates the specific wavelength at which an observation or measurement is made or recorded.
-
D.
riverbedDepth
Indicates the depth or vertical distance from the water surface to the bottom of a river at a given location or time.
-
E.
spectralResolution
Indicates the fineness with which a system can distinguish or separate different wavelengths or frequencies within a spectrum.
- 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_69a494267b4c819088c97a59182bf56a |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bd32c5f48190b4e2d39fa052cbb7 |
completed | March 1, 2026, 10:26 p.m. |
| PD | Predicate disambiguation | batch_69a4bb59ca6c81908597a81646674aaa |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:45 p.m.