Triple
T9631348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quebec general election |
E232809
|
entity |
| Predicate | primaryIssueAreas |
P19540
|
FINISHED |
| Object | language policy in Quebec |
—
|
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: language policy in Quebec | Statement: [Quebec general election, primaryIssueAreas, language policy in Quebec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryIssueAreas Context triple: [Quebec general election, primaryIssueAreas, language policy in Quebec]
-
A.
primaryIssue
Indicates that the related item is the main or most important issue among a set of issues.
-
B.
keyIssueArea
chosen
Indicates that something is a primary topic, domain, or field that is central or especially important within a broader context or discussion.
-
C.
primaryArea
Indicates that one entity is the main or most important area, domain, or field associated with another entity.
-
D.
commonPolicyArea
Indicates that two entities share the same policy domain, topic, or area of regulatory or legislative focus.
-
E.
thematicArea
Indicates the subject or item is associated with, or falls under, a particular thematic area or topic of focus.
- 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_69ca848940cc8190b97cec654cb3bb4a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b2621408190bfe2ea5a05359ee0 |
completed | April 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69ccd5acfa5c8190aaba3cf548723604 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:11 p.m.