Triple
T35369074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rick Vaive |
E1021716
|
entity |
| Predicate | scored50GoalsInSeasonFor |
P110425
|
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: [Rick Vaive, scored50GoalsInSeasonFor, Toronto Maple Leafs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scored50GoalsInSeasonFor Context triple: [Rick Vaive, scored50GoalsInSeasonFor, Toronto Maple Leafs]
-
A.
scored50GoalsInASeason
chosen
Indicates that an entity (typically an athlete) achieved a total of 50 goals within a single season.
-
B.
scored30GoalsInSeason
Indicates that an entity (typically an athlete) achieved a total of 30 goals during a single competitive season.
-
C.
consecutive50GoalSeasons
Indicates that an entity has achieved 50 or more goals in each of multiple consecutive seasons.
-
D.
scoredGoalSeason
Indicates that an entity scored a goal during a specified season.
-
E.
teamWith50GoalSeason
Indicates that a team has achieved at least one season in which it scored 50 or more goals.
- 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_69f76df000488190ab7c97f565677055 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:03 p.m.