Triple
T23642188
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017 Conservative Party of Canada leadership election |
E583928
|
entity |
| Predicate | finalPointsForRunnerUp |
P38172
|
FINISHED |
| Object | 16,577 |
—
|
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: 16,577 | Statement: [2017 Conservative Party of Canada leadership election, finalPointsForRunnerUp, 16,577]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: finalPointsForRunnerUp Context triple: [2017 Conservative Party of Canada leadership election, finalPointsForRunnerUp, 16,577]
-
A.
runnersUpPoints
Indicates the number of points awarded to an entity for finishing as a runner-up in a competition or ranking.
-
B.
runnerUpScore
chosen
Indicates the score achieved by the participant or entity that finished in second place in a competition or ranking.
-
C.
secondRoundRunnerUp
Indicates that an entity finished in third place (runner-up to the runner-up) in the second round of a competition or selection process.
-
D.
gamesWonByRunnerUp
Indicates the number of games won by the runner-up in a competition or match.
-
E.
finalSecondLegScore
Indicates the score achieved in the second leg of a two-leg competition or matchup once that leg is completed.
- 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_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. |
Created at: April 17, 2026, 6:48 p.m.