Triple
T11861520
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clean, Old-Fashioned Hate |
E282168
|
entity |
| Predicate | primaryColorsGeorgia |
P24916
|
FINISHED |
| Object | red and black |
—
|
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: red and black | Statement: [Clean, Old-Fashioned Hate, primaryColorsGeorgia, red and black]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryColorsGeorgia Context triple: [Clean, Old-Fashioned Hate, primaryColorsGeorgia, red and black]
-
A.
primaryColorPalette
Indicates the set of main or dominant colors associated with an entity, typically used as its core color scheme.
-
B.
originalColors
Indicates that something retains or is associated with its initial, unaltered set of colors.
-
C.
primaryColour
chosen
Indicates that one entity is the main or dominant color characteristic of another entity.
-
D.
nationalColorsRepresented
Indicates that the national colors of an entity are visibly included or symbolically expressed in another entity or context.
-
E.
colors
Indicates that one entity assigns, describes, or provides the color or colors 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a69b16bc8190999a0c1240f9ce6a |
completed | April 10, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69d8a2573dbc8190ab432e8e28fde6cc |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.