Triple
T15016381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of the Second Spanish Republic |
E377968
|
entity |
| Predicate | associatedColorMeaning |
P46606
|
FINISHED |
| Object | red representing Castile |
—
|
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 representing Castile | Statement: [flag of the Second Spanish Republic, associatedColorMeaning, red representing Castile]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedColorMeaning Context triple: [flag of the Second Spanish Republic, associatedColorMeaning, red representing Castile]
-
A.
starColorSymbolism
Indicates how the color of a star is associated with particular symbolic meanings or themes.
-
B.
associatedColour
Indicates that one entity is linked to another as its characteristic or representative colour.
-
C.
colorHasMeaning
chosen
Indicates that a particular color is associated with or conveys a specific meaning, symbolism, or significance.
-
D.
primaryColorSymbolism
Indicates how a primary color is symbolically associated with particular meanings, emotions, or concepts in a given 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_69d85cd3a3c881908c71fc424d459c17 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded7633fcc8190b2231f43252bc46f |
completed | April 15, 2026, 12:10 a.m. |
| PD | Predicate disambiguation | batch_69de9a6531a88190acde65199a477350 |
completed | April 14, 2026, 7:49 p.m. |
Created at: April 10, 2026, 2:55 a.m.