Triple
T272279
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Officer of the Order of Canada |
E5658
|
entity |
| Predicate | scopeOfContribution |
P9961
|
FINISHED |
| Object | national |
—
|
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: national | Statement: [Officer of the Order of Canada, scopeOfContribution, national]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scopeOfContribution Context triple: [Officer of the Order of Canada, scopeOfContribution, national]
-
A.
scopeOfUse
Indicates the range, context, or conditions under which something is intended, allowed, or applicable to be used.
-
B.
publicationScope
Indicates the extent, audience, or boundaries within which something (such as a work, data, or information) is made publicly available or distributed.
-
C.
notableContribution
Indicates that an entity has made a significant, recognized contribution to another entity, field, work, or endeavor.
-
D.
contributeTo
Indicates that one entity provides support, resources, or effort that helps bring about, enhance, or maintain another entity, outcome, or state.
-
E.
fieldOfWork
Indicates the professional or academic domain in which an entity is primarily engaged or specializes.
- 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_69a25853594c8190b05ec3a586ec88bf |
completed | Feb. 28, 2026, 2:52 a.m. |
| NER | Named-entity recognition | batch_69a25e69a9248190b9e7959b43223baa |
completed | Feb. 28, 2026, 3:18 a.m. |
| PD | Predicate disambiguation | batch_69a25b721180819080d43c43fcbccf87 |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25e68f0408190bfc851c32d6eebf3 |
completed | Feb. 28, 2026, 3:18 a.m. |
Created at: Feb. 28, 2026, 2:57 a.m.