Triple
T4543855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1967–68 ABA season |
E109999
|
entity |
| Predicate | topRebounderReboundsPerGame |
P22437
|
FINISHED |
| Object | 15.6 |
—
|
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: 15.6 | Statement: [1967–68 ABA season, topRebounderReboundsPerGame, 15.6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: topRebounderReboundsPerGame Context triple: [1967–68 ABA season, topRebounderReboundsPerGame, 15.6]
-
A.
statRebounds
chosen
Indicates the number of rebounds an entity (typically a player or team) records in a game or over a specified period.
-
B.
careerReboundsPerGame
Indicates the average number of rebounds a player records per game over the course of their entire career.
-
C.
reboundsLeaderTeam
Indicates that a team is the leading team in total rebounds in a given game, season, or competition context.
-
D.
franchiseReboundsLeader
Indicates the player who holds the record for the most rebounds in a franchise’s history.
-
E.
NBAReboundingLeaderYears
Indicates the years in which an entity was the NBA leader in rebounds.
- 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_69bd4412524c8190be5bcc9ddee91848 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57d517e881909c3d23ed4453b0a7 |
completed | March 20, 2026, 2:21 p.m. |
| PD | Predicate disambiguation | batch_69bd5220e40481908ca2d7e2c43d8531 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:05 p.m.