Triple
T29421177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siniristilippu |
E746159
|
entity |
| Predicate | hasColorSpecification |
P48842
|
FINISHED |
| Object | blue defined by Finnish standards |
—
|
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: blue defined by Finnish standards | Statement: [Siniristilippu, hasColorSpecification, blue defined by Finnish standards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasColorSpecification Context triple: [Siniristilippu, hasColorSpecification, blue defined by Finnish standards]
-
A.
hasColorInfo
chosen
Indicates that an entity is associated with specific color-related information or attributes.
-
B.
hasColorType
Indicates that an entity is associated with a specific category or type of color.
-
C.
hasColorStructure
Indicates that an entity possesses a specific arrangement or pattern of colors.
-
D.
hasColorModel
Indicates that an entity uses or is associated with a particular color representation model (such as RGB, CMYK, or HSV) for defining its colors.
-
E.
isColor
Indicates that one entity represents the color attribute or hue of another entity.
- 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_69f0a79f6d5c8190a350baed0157e06f |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a0067cde0f08190b2cd93af5f00d519 |
completed | May 10, 2026, 11:11 a.m. |
| PD | Predicate disambiguation | batch_6a0065820c8c8190994734433c64a30a |
completed | May 10, 2026, 11:01 a.m. |
Created at: April 28, 2026, 3:05 p.m.