Triple
T27546428
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2000 NBA All-Star Game |
E695373
|
entity |
| Predicate | TimDuncanRebounds |
P22437
|
FINISHED |
| Object | 14 |
—
|
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: 14 | Statement: [2000 NBA All-Star Game, TimDuncanRebounds, 14]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: TimDuncanRebounds Context triple: [2000 NBA All-Star Game, TimDuncanRebounds, 14]
-
A.
TimDuncanPoints
Indicates the number of points scored by Tim Duncan in a game or over a specified period.
-
B.
timDuncanPointsGame1
Indicates the number of points that Tim Duncan scored in Game 1 of a particular series or matchup.
-
C.
careerReboundsPerGame
Indicates the average number of rebounds a player records per game over the course of their entire career.
-
D.
franchiseReboundsLeader
Indicates the player who holds the record for the most rebounds in a franchise’s history.
-
E.
statRebounds
chosen
Indicates the number of rebounds an entity (typically a player or team) records in a game or over a specified period.
- 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_69ef5386c3e08190bfe33aa326e1f72b |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f6359e3d3c81909814e2f0a7fb0ea9 |
completed | May 2, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f631871c888190bf29466fe4254e51 |
completed | May 2, 2026, 5:16 p.m. |
Created at: April 27, 2026, 1:33 p.m.