Triple
T102444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Basketball Association |
E2067
|
entity |
| Predicate | numberOfUSATeams |
P3760
|
FINISHED |
| Object | 29 |
—
|
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: 29 | Statement: [National Basketball Association, numberOfUSATeams, 29]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUSATeams Context triple: [National Basketball Association, numberOfUSATeams, 29]
-
A.
numberOfTeamsInUnitedStates
chosen
Indicates the total count of teams that are located within or belong to the United States.
-
B.
numberOfTeamsInCanada
Indicates the total count of teams that are located in Canada.
-
C.
numberOfAmericanLeagueTeams
Indicates the total count of teams that belong to the American League.
-
D.
nationalFootballTeam
Indicates that one entity is the official football (soccer) team representing the other entity at the national level.
-
E.
collegeTeam
Indicates that one entity is a sports team that represents or is affiliated with a particular college or university.
- 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a2563a6ff48190bec582fb2f99b7af |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.