Triple
T10132965
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Green Red |
E226783
|
entity |
| Predicate | colorFieldCharacteristic |
P92152
|
FINISHED |
| Object | large uniform color areas |
—
|
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: large uniform color areas | Statement: [Blue Green Red, colorFieldCharacteristic, large uniform color areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: colorFieldCharacteristic Context triple: [Blue Green Red, colorFieldCharacteristic, large uniform color areas]
-
A.
catalogCharacteristic
Indicates that a catalog has a specific characteristic or attribute associated with it.
-
B.
codeCharacteristic
Indicates that one piece of code possesses a specific property, feature, or quality in relation to another referenced aspect.
-
C.
colors
Indicates that one entity assigns, describes, or provides the color or colors of another entity.
-
D.
colorGrade
Indicates the qualitative or categorical assessment of an entity’s color according to a defined grading scale.
-
E.
capeColor
Indicates the color attribute associated with a cape worn or possessed by an entity.
- 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_69ca8433ec308190b8b25a6fe359c34c |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cdd336cbf48190b647c69675d0b06f |
completed | April 2, 2026, 2:23 a.m. |
| PD | Predicate disambiguation | batch_69cd4ba1d360819087698d04a53cc87e |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4fed19d481909d2c7ff1114664b6 |
completed | April 1, 2026, 5:03 p.m. |
Created at: March 30, 2026, 9:06 p.m.