Triple
T1336219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Missouri–Kansas–Texas Railroad |
E28754
|
entity |
| Predicate | corporateColor |
P27889
|
FINISHED |
| Object | green |
—
|
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: green | Statement: [Missouri–Kansas–Texas Railroad, corporateColor, green]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: corporateColor Context triple: [Missouri–Kansas–Texas Railroad, corporateColor, green]
-
A.
logoColor
Indicates the color or primary color scheme used in an entity’s logo.
-
B.
serviceBranchColor
Indicates the specific color associated with a particular branch of service (e.g., military or organizational branch) as its identifying or representative color.
-
C.
logoBackgroundColors
Indicates the background color or colors used behind a logo in its visual representation.
-
D.
corpsColour
Indicates the specific color associated with a military corps or unit.
-
E.
teamColor
Indicates the association between a team and the color that represents or identifies it.
- 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_69a498561a508190a3e1bc137c2b866a |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c1ecb5208190a9eadda113c91e66 |
completed | March 1, 2026, 10:47 p.m. |
| PD | Predicate disambiguation | batch_69a4bef174708190a07bbc697fe19a2d |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c1bf31988190a659f48fe018f4bc |
completed | March 1, 2026, 10:46 p.m. |
Created at: March 1, 2026, 7:55 p.m.