Triple
T4576206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DLP technology |
E123145
|
entity |
| Predicate | colorGenerationMethod |
P17351
|
FINISHED |
| Object | color wheel in many single-chip designs |
—
|
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: color wheel in many single-chip designs | Statement: [DLP technology, colorGenerationMethod, color wheel in many single-chip designs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorGenerationMethod Context triple: [DLP technology, colorGenerationMethod, color wheel in many single-chip designs]
-
A.
colorEncodingMethod
chosen
Indicates the method or scheme used to represent or encode color information.
-
B.
colorVarietyOf
Indicates that one entity represents a specific color variant or color option of another entity.
-
C.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
D.
colorDisplay
Indicates that one entity presents, shows, or renders the color associated with another entity.
-
E.
colorTheory
Indicates a relationship where principles or concepts about how colors interact, combine, or affect perception are applied or referenced between entities.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58dfe3508190b21836079e951a3c |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:10 p.m.