Triple
T23642184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 Conservative Party of Canada leadership election |
E583928
|
entity |
| Predicate | pointsPerRiding |
P153006
|
FINISHED |
| Object | 100 |
—
|
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: 100 | Statement: [2017 Conservative Party of Canada leadership election, pointsPerRiding, 100]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsPerRiding Context triple: [2017 Conservative Party of Canada leadership election, pointsPerRiding, 100]
-
A.
numberOfRiders
Indicates the total count of riders associated with a given entity or event.
-
B.
ridershipLevel
Indicates the magnitude or intensity of usage by riders or passengers for a given service, route, or system.
-
C.
pointsEarnedFrom
Indicates the number of points that an entity has received as a result of another specified source, action, or event.
-
D.
distancePerRace
Indicates the total distance covered in a single race event or instance.
-
E.
pointsLeader
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
- 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_69e248fefafc81909656921192f30e80 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b2821cb881909b1ab77aa77208e0 |
completed | April 29, 2026, 7:25 a.m. |
| PD | Predicate disambiguation | batch_69f118d7903c8190bb590a71771e93af |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f1233300bc8190ac1639bdca1d7d99 |
completed | April 28, 2026, 9:14 p.m. |
Created at: April 17, 2026, 6:48 p.m.