Triple
T49833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basketball Association of America |
E979
|
entity |
| Predicate | teamCountAtPeak |
P2657
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [Basketball Association of America, teamCountAtPeak, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamCountAtPeak Context triple: [Basketball Association of America, teamCountAtPeak, 12]
-
A.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
-
B.
hallOfFamePlayersCount
Indicates the number of players associated with an entity who have been inducted into a hall of fame.
-
C.
numberOfPositions
Indicates the total count of distinct positions or roles associated with a given entity.
-
D.
crewCountApproximate
Indicates that the relationship specifies an estimated or approximate number of crew members associated with an entity.
-
E.
heldTallestStructureTitleUntil
Indicates that one structure held the title of being the tallest in a given context up to and including a specified end time.
- 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_69a2480baefc81909951b14058479aa2 |
completed | Feb. 28, 2026, 1:42 a.m. |
| NER | Named-entity recognition | batch_69a24b6c9eb88190b2fe85e427f4177a |
completed | Feb. 28, 2026, 1:57 a.m. |
| PD | Predicate disambiguation | batch_69a24ac0fb088190b7a5e87817e8e747 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24b6b7638819095a86e2151635a02 |
completed | Feb. 28, 2026, 1:56 a.m. |
Created at: Feb. 28, 2026, 1:47 a.m.