Triple
T2572660
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Black Canadians |
E57698
|
entity |
| Predicate | faceIssues |
P13650
|
FINISHED |
| Object | systemic racism in Canada |
—
|
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: systemic racism in Canada | Statement: [Black Canadians, faceIssues, systemic racism in Canada]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceIssues Context triple: [Black Canadians, faceIssues, systemic racism in Canada]
-
A.
facesChallenge
Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
-
B.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
-
C.
facingIssue
chosen
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
-
D.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
E.
faceliftFeature
Indicates that one entity is a specific feature, component, or aspect involved in a facelift procedure or facelift-related modification of the other 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3853c848190970e8a2da16d726d |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.