Triple
T1502721
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NBA All-Defensive Team |
E33831
|
entity |
| Predicate | totalPlayersPerSeason |
P3190
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [NBA All-Defensive Team, totalPlayersPerSeason, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalPlayersPerSeason Context triple: [NBA All-Defensive Team, totalPlayersPerSeason, 10]
-
A.
totalMatchesPerSeason
Indicates the total number of matches associated with an entity within a single season.
-
B.
divisionGamesPerSeason
Indicates the number of games played in a particular division during a single season.
-
C.
numberOfSeasonsWithTeam
Indicates the total count of seasons an entity (e.g., a player or coach) has spent with a particular team.
-
D.
rosterSizeRegularSeason
chosen
Indicates the number of players a team is allowed or has on its roster during the regular season.
-
E.
coachOfYearSeason
Indicates that a person was recognized as the coach of the year for a specific sports 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_69a885f352a4819099b24ff15489dede |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90584b8b881908e112c7e59163812 |
completed | March 5, 2026, 4:24 a.m. |
| PD | Predicate disambiguation | batch_69a88727ce48819089b482cdc25453d1 |
completed | March 4, 2026, 7:25 p.m. |
Created at: March 4, 2026, 7:24 p.m.