Triple
T10425300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pavel Datsyuk |
E245769
|
entity |
| Predicate | numberOfTimesWonLadyByngMemorialTrophy |
P93519
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Pavel Datsyuk, numberOfTimesWonLadyByngMemorialTrophy, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTimesWonLadyByngMemorialTrophy Context triple: [Pavel Datsyuk, numberOfTimesWonLadyByngMemorialTrophy, 4]
-
A.
wonLadyByngMemorialTrophy
Indicates that the subject has been awarded the Lady Byng Memorial Trophy.
-
B.
ArtRossTrophy
Indicates that the subject has been awarded the Art Ross Trophy, recognizing them as the leading point scorer in a National Hockey League regular season.
-
C.
NorrisTrophyWins
Indicates the number of times an entity has won the Norris Trophy, awarded annually to the NHL’s top defenseman.
-
D.
presidentsTrophyWins
Indicates the number of times an entity has won the Presidents' Trophy, awarded for the best regular-season record in a league.
-
E.
LadyByngTrophyWinnerTeam
Indicates the team for which a given Lady Byng Memorial Trophy winner was playing when they received the award.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea48cb348190ad4432f263300592 |
completed | April 7, 2026, 11:28 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb9d3648190aaabed901f22a8c0 |
completed | April 7, 2026, 10:43 a.m. |
| PDg | Predicate description generation | batch_69d4e91de3088190ae89cbb12fb29db8 |
completed | April 7, 2026, 11:23 a.m. |
Created at: April 6, 2026, 12:12 p.m.