Triple
T37859042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Monta Ellis |
E944271
|
entity |
| Predicate | seasonPointsPerGameHigh |
P52811
|
FINISHED |
| Object | 25.5 points per game in 2009-2010 NBA season |
—
|
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: 25.5 points per game in 2009-2010 NBA season | Statement: [Monta Ellis, seasonPointsPerGameHigh, 25.5 points per game in 2009-2010 NBA season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonPointsPerGameHigh Context triple: [Monta Ellis, seasonPointsPerGameHigh, 25.5 points per game in 2009-2010 NBA season]
-
A.
careerPointsPerGame
Indicates the average number of points an individual scores per game over the course of their entire career.
-
B.
maxPointsPerGame
Indicates the maximum number of points an entity can score or is allowed to score in a single game.
-
C.
pointsPerGame
chosen
Indicates the average number of points an entity scores per game over a given set of games.
-
D.
seasonPointsRecordSet
Indicates that a new record for total points scored in a season has been achieved or established.
-
E.
mostPointsPerGamePlayer
Indicates the player who has the highest average number of points scored per game within a given context or season.
- 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_69f76eee2f9c8190b1272aa2ee55ebf5 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd9ff026a48190bfec33deeb3b2c43 |
completed | May 8, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69fd97d805bc8190ba12f429d3ad04c7 |
completed | May 8, 2026, 7:59 a.m. |
Created at: May 3, 2026, 4:19 p.m.