Triple
T15064207
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yablonovitch limit in light trapping |
E379712
|
entity |
| Predicate | maximumEnhancementFactor |
P117177
|
FINISHED |
| Object | 4n^2 |
—
|
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: 4n^2 | Statement: [Yablonovitch limit in light trapping, maximumEnhancementFactor, 4n^2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maximumEnhancementFactor Context triple: [Yablonovitch limit in light trapping, maximumEnhancementFactor, 4n^2]
-
A.
maximumEfficiency
Indicates that an entity operates at its highest possible level of performance or productivity under given conditions.
-
B.
maximumIntensity
Indicates the greatest level or strength that a quantity, effect, or signal can reach within a given context.
-
C.
maximumBrightness
Indicates the highest level of brightness that an entity can reach or exhibit.
-
D.
maximumGradient
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
-
E.
maximumResolution
Indicates the highest level of detail or fineness at which something (such as an image, display, or measurement) can be represented or processed.
- F. None of above. chosen
Provenance (4 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee803ac81908bb7d66e49c2eb72 |
completed | April 15, 2026, 12:42 a.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:02 a.m.