Triple
T26700414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Morgan Rielly |
E673137
|
entity |
| Predicate | hasPlayedOnlyForTeamInNHL |
P68837
|
FINISHED |
| Object | Toronto Maple Leafs |
—
|
NE NERFINISHED |
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: Toronto Maple Leafs | Statement: [Morgan Rielly, hasPlayedOnlyForTeamInNHL, Toronto Maple Leafs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlayedOnlyForTeamInNHL Context triple: [Morgan Rielly, hasPlayedOnlyForTeamInNHL, Toronto Maple Leafs]
-
A.
numberOfNHLTeamsPlayedFor
Indicates the total count of distinct NHL teams for which a given player has played.
-
B.
playedNHLGamesFor
Indicates that a person has participated in one or more official National Hockey League games as a player for a specified team.
-
C.
NHLTeamsPlayedFor
Indicates that there exists a professional ice hockey playing relationship where a player has been a member of, and played for, one or more specified NHL teams.
-
D.
playedEntireNHLCareerFor
chosen
Indicates that a person spent their entire National Hockey League playing career exclusively with a single team.
-
E.
playedInKHLTeam
Indicates that a person has been a player for a specific team in the Kontinental Hockey League (KHL).
- 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_69eecda2b49c8190a6c481cfc4c07954 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69f6afebd7ec8190ab696f363d84abf0 |
completed | May 3, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69f6aca204148190850a3dc325bc07b7 |
completed | May 3, 2026, 2:02 a.m. |
Created at: April 27, 2026, 3:31 a.m.