Triple
T745502
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cabinet of Canada |
E15331
|
entity |
| Predicate | meetsInCamera |
P18585
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Cabinet of Canada, meetsInCamera, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meetsInCamera Context triple: [Cabinet of Canada, meetsInCamera, true]
-
A.
capturedIn
Indicates that one entity was taken prisoner, seized, or otherwise brought under control within the context, location, or event represented by another entity.
-
B.
meetsAs
Indicates that two entities encounter or come together at the same place and time, typically in a planned or recognized interaction.
-
C.
meets
Indicates that two or more entities come together at the same place and time, typically for interaction or a shared purpose.
-
D.
meetsUnder
Indicates that one entity encounters or comes together with another entity in a context where it is subordinate to, governed by, or occurring within the scope or authority of a third entity or condition.
-
E.
hasAperture
Indicates that one entity possesses or is characterized by a specific opening, gap, or aperture.
- 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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a61217b881908592096b1edacb8a |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ff10608190bfd60b4a1cb38f7d |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a57267c481909790a1fda3fced08 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.