Triple
T21794039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David O'Neil Thompson |
E538045
|
entity |
| Predicate | scoredCareerHighPointsInSingleGame |
P145670
|
FINISHED |
| Object | 73 |
—
|
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: 73 | Statement: [David O'Neil Thompson, scoredCareerHighPointsInSingleGame, 73]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredCareerHighPointsInSingleGame Context triple: [David O'Neil Thompson, scoredCareerHighPointsInSingleGame, 73]
-
A.
scored70PointsInSingleGame
Indicates that an entity achieved a total of 70 points in a single game or match.
-
B.
scored71PointsInSingleGame
Indicates that an entity achieved a total of 71 points in a single game.
-
C.
heldNBAAllTimeScoringRecordUntil
Indicates that one entity was the NBA’s all-time leading scorer up to a certain time, after which another entity surpassed that record.
-
D.
hitsInSingleGameRecord
Indicates that an entity holds the record for the most hits achieved in a single game.
-
E.
NBA_careerPoints
Indicates the total number of points a player has scored over the course of their NBA career.
- F. None of above. chosen
Provenance (4 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_69e0c4733f4081909a86622e7e6d15d2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0622329b08190b8cd9be714aca456 |
completed | April 28, 2026, 7:30 a.m. |
| PD | Predicate disambiguation | batch_69e6be751ce881909badced245ef76c7 |
completed | April 21, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69e6c3a2898881909748935cf92f898c |
completed | April 21, 2026, 12:24 a.m. |
Created at: April 16, 2026, 6:52 p.m.