Triple
T15999204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NFL 2K |
E388052
|
entity |
| Predicate | instanceOf |
P0
|
FINISHED |
| Object | American football video game series |
C36806
|
CONCEPT FINISHED |
How this triple was built (1 step)
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.
CD
Concept disambiguation
gpt-5-mini-2025-08-07
Target class: American football video game series Context triple: [NFL 2K, instanceOf, American football video game series]
-
A.
American football television program
An American football television program is a broadcast show that presents live or recorded American football games, along with commentary, analysis, highlights, and related features for viewers.
-
B.
American football game
An American football game is a competitive sporting event in which two teams attempt to advance an oval-shaped ball into the opponent’s end zone through a series of timed plays to score points and determine a winner.
-
C.
American football organization
An American football organization is an entity that manages, promotes, and governs American football activities, including teams, competitions, player development, and related operations within a defined scope or region.
-
D.
series of National Football League games
A series of National Football League games is an ordered collection of NFL matchups, typically grouped by a common context such as season, rivalry, playoff round, or special event, and treated as a cohesive competitive or narrative unit.
-
E.
American football application
An American football application is a software system that provides tools and features for managing, analyzing, and engaging with American football games, teams, players, and related statistics.
- F. None of above. chosen
Provenance (1 batch)
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_69d86daa562c81908aacc179c0fe8fb5 |
completed | April 10, 2026, 3:25 a.m. |
Created at: April 10, 2026, 4:55 a.m.