Triple
T13213709
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1986–87 NBA season |
E314554
|
entity |
| Predicate | scoringLeaderPointsPerGame |
P52811
|
FINISHED |
| Object | 37.1 |
—
|
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: 37.1 | Statement: [1986–87 NBA season, scoringLeaderPointsPerGame, 37.1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoringLeaderPointsPerGame Context triple: [1986–87 NBA season, scoringLeaderPointsPerGame, 37.1]
-
A.
scoringLeaderPoints
Indicates the number of points scored by the leading scorer in a game, season, or competition.
-
B.
scoringLeaderAssists
Indicates that the entity identified as the scoring leader in a game or season also recorded the most assists (or a specified number of assists) in that context.
-
C.
scoringLeaderGoals
Indicates that the subject is the leading scorer in terms of goals, having scored more goals than any other relevant participant in the given context.
-
D.
pointsPerGame
chosen
Indicates the average number of points an entity scores per game over a given set of games.
-
E.
pointsScored
Indicates the number of points an entity has earned or achieved in a particular event, game, or context.
- 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_69d806aee7308190b70a237ba2a6e3e1 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc938f081909f123bdf1263ff7f |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:17 p.m.