Triple
T7180537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patrick Marleau |
E167434
|
entity |
| Predicate | NHLGamesPlayedRecordTotal |
P57791
|
FINISHED |
| Object | 1779 |
—
|
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: 1779 | Statement: [Patrick Marleau, NHLGamesPlayedRecordTotal, 1779]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NHLGamesPlayedRecordTotal Context triple: [Patrick Marleau, NHLGamesPlayedRecordTotal, 1779]
-
A.
NHLGamesPlayedForTeam
Indicates that a person has participated in one or more official NHL games as a player for the specified team.
-
B.
gamesPlayedInNHL
Indicates the number of games an individual has participated in within the National Hockey League (NHL).
-
C.
NHLPlayoffAppearances
Indicates that a team has qualified for and participated in the NHL postseason playoffs one or more times.
-
D.
careerNHLGamesPlayed
chosen
Indicates the total number of NHL games an individual has played over the course of their entire career.
-
E.
numberOfNHLTeamsPlayedFor
Indicates the total count of distinct NHL teams for which a given player has played.
- 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_69c6888a7c548190a3d39b52a393080f |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:49 p.m.