Triple
T31068134
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quebec in the Parliament of Canada |
E791732
|
entity |
| Predicate | hasRepresentationUnit |
P70325
|
FINISHED |
| Object | federal riding 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: federal riding in Quebec | Statement: [Quebec in the Parliament of Canada, hasRepresentationUnit, federal riding in Quebec]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRepresentationUnit Context triple: [Quebec in the Parliament of Canada, hasRepresentationUnit, federal riding in Quebec]
-
A.
hasUnitOf
Indicates that a quantity, measurement, or value is expressed in terms of a specific unit.
-
B.
representationUnit
chosen
Indicates a relationship where one entity serves as the representational unit or basic representational component used to express, encode, or stand in for another entity or concept.
-
C.
hasUnits
Indicates that a quantity, measurement, or value is expressed in a specified system or type of units.
-
D.
hasUnitIn
Indicates that one entity is contained or measured within another as a unit, specifying a unit-of-measure or component relationship.
-
E.
isAUnitOf
Indicates that one entity functions as a unit or standard measure in which the other entity is quantified or expressed.
- 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_69f224cc0c5c81908404f087bff92997 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a00cda99c908190980e0bf54cb2e2a4 |
completed | May 10, 2026, 6:25 p.m. |
| PD | Predicate disambiguation | batch_6a00cd1635b08190a791ecfcf87a1d54 |
completed | May 10, 2026, 6:23 p.m. |
Created at: April 29, 2026, 9:01 p.m.