Triple
T1180320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GPON |
E25120
|
entity |
| Predicate | videoOverlayWavelength |
P5242
|
FINISHED |
| Object | 1550 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: 1550 nm | Statement: [GPON, videoOverlayWavelength, 1550 nm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: videoOverlayWavelength Context triple: [GPON, videoOverlayWavelength, 1550 nm]
-
A.
videoModulation
Indicates a relationship where one entity alters or controls the characteristics of a video signal or stream, such as its amplitude, frequency, or encoding parameters.
-
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.
visualEffect
Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
-
D.
hasObservationWavelength
Indicates the specific wavelength at which an observation or measurement is made or recorded.
-
E.
mediaAspect
Indicates the specific aspect ratio or dimensional proportion of a media item in relation to its width and height.
- 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.