Triple
T7187242
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | American football |
E167602
|
entity |
| Predicate | typicalTeamSizeOnField |
P3668
|
FINISHED |
| Object | 11 players per team |
—
|
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: 11 players per team | Statement: [American football, typicalTeamSizeOnField, 11 players per team]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTeamSizeOnField Context triple: [American football, typicalTeamSizeOnField, 11 players per team]
-
A.
typicalTeamSize
chosen
Indicates the usual or most common number of members that make up a given team.
-
B.
usesNumberOfPlayersOnFieldPerTeam
Indicates that the relationship specifies or depends on how many players each team has on the field at a given time.
-
C.
playersPerSideOnField
Indicates the number of players from each team that are simultaneously present on the field during play.
-
D.
sportNumberOfPlayersOnTeam
Indicates the number of players that make up a single team in a given sport.
-
E.
rosterSize
Indicates the total number of individuals included on a given roster.
- 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_69c6888b5248819090499a884ee3ec39 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e9b045c48190b27b2d6f7c11026f |
completed | March 27, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69c6e74fb0f48190b2ad4dd4efdd241a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:50 p.m.