Triple
T6658591
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scott Niedermayer |
E151410
|
entity |
| Predicate | wonWorldCupOfHockeyYear |
P19046
|
FINISHED |
| Object | 2004 |
—
|
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: 2004 | Statement: [Scott Niedermayer, wonWorldCupOfHockeyYear, 2004]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonWorldCupOfHockeyYear Context triple: [Scott Niedermayer, wonWorldCupOfHockeyYear, 2004]
-
A.
WorldCupOfHockeyWinner
chosen
Indicates the team that won the specified edition of the World Cup of Hockey.
-
B.
worldCupOfHockeyRunnerUpYear
Indicates the year in which a given team or country finished as the runner-up in the World Cup of Hockey tournament.
-
C.
worldCupOfHockeyTitles
Indicates the number of World Cup of Hockey championship titles an entity has won.
-
D.
WorldCupOfHockey
Indicates that there is a relationship involving participation in, hosting of, or association with the World Cup of Hockey tournament.
-
E.
worldCupOfHockeyBestResult
Indicates the best performance or highest achievement an entity has attained in the World Cup of Hockey tournament.
- 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_69c687f5fac48190a09e4838d9c6b45d |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6cc9d53848190ac75523c157249c6 |
completed | March 27, 2026, 6:29 p.m. |
| PD | Predicate disambiguation | batch_69c6ad071b0081909b96dd4b93414bd1 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:01 p.m.