Triple
T30358406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | X-Trans CMOS |
E772206
|
entity |
| Predicate | hasGreenPixelDistribution |
P175266
|
FINISHED |
| Object | more randomized than Bayer pattern |
—
|
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: more randomized than Bayer pattern | Statement: [X-Trans CMOS, hasGreenPixelDistribution, more randomized than Bayer pattern]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGreenPixelDistribution Context triple: [X-Trans CMOS, hasGreenPixelDistribution, more randomized than Bayer pattern]
-
A.
hasGreenType
Indicates that an entity possesses or is associated with a type classified as green.
-
B.
hasRGB
Indicates that an entity possesses or is associated with a specific RGB (red, green, blue) color value.
-
C.
hasNumberOfColors
Indicates the quantity of distinct colors associated with an entity.
-
D.
hasGreenRuns
Indicates that an entity possesses or includes ski runs that are classified as green (i.e., beginner-level).
-
E.
hasColorRange
Indicates that an entity possesses or is associated with a specific span or set of colors, rather than a single discrete color.
- 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_69f2248c6f5c8190a6177842bf791a3c |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6cee547108190ad3bc84297d8f516 |
completed | May 3, 2026, 4:28 a.m. |
| PD | Predicate disambiguation | batch_69f6cc1188708190b8f0f56e595e6057 |
completed | May 3, 2026, 4:16 a.m. |
| PDg | Predicate description generation | batch_69f6cee3604c81908a07eade2f39064e |
completed | May 3, 2026, 4:28 a.m. |
Created at: April 29, 2026, 7:57 p.m.