Triple
T25077751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gulf, Mobile and Ohio Railroad |
E628097
|
entity |
| Predicate | hadCorporateColorScheme |
P29272
|
FINISHED |
| Object | red and maroon |
—
|
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 maroon | Statement: [Gulf, Mobile and Ohio Railroad, hadCorporateColorScheme, red and maroon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadCorporateColorScheme Context triple: [Gulf, Mobile and Ohio Railroad, hadCorporateColorScheme, red and maroon]
-
A.
corporateColor
Indicates the official color or color scheme that represents a corporation’s brand or identity.
-
B.
hasColourScheme
chosen
Indicates that an entity is associated with a particular set or pattern of colors used in its design or appearance.
-
C.
formerColorScheme
Indicates that an entity previously used a particular color scheme but no longer does so.
-
D.
usesBrandColor
Indicates that one entity applies or displays another entity’s official brand color in its appearance, design, or materials.
-
E.
officialColor
Indicates the color that is formally designated or recognized as the official one for an 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_69e2ff2e73f881909992bf3eda5c25cb |
completed | April 18, 2026, 3:49 a.m. |
| NER | Named-entity recognition | batch_69f45d1ad0ec8190831b9d6d28a6644a |
completed | May 1, 2026, 7:58 a.m. |
| PD | Predicate disambiguation | batch_69f442c861188190967655c6d8012380 |
completed | May 1, 2026, 6:06 a.m. |
Created at: April 18, 2026, 6:21 a.m.