Triple
T2571894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CFL |
E57681
|
entity |
| Predicate | usesNumberOfPlayersOnFieldPerTeam |
P39863
|
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: [CFL, usesNumberOfPlayersOnFieldPerTeam, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesNumberOfPlayersOnFieldPerTeam Context triple: [CFL, usesNumberOfPlayersOnFieldPerTeam, 12]
-
A.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
numberOfPlayersOnIcePerTeam
Indicates the count of players from a single team who are on the ice at the same time during play.
-
C.
allowsOveragePlayers
Indicates that a context, rule, or system permits participation or inclusion of players who exceed a specified age limit.
-
D.
numberOfTeamsVariesBetween
Indicates that the count of teams involved changes within a specified range or across different instances or conditions.
-
E.
teamCountType
Indicates how the number of teams is categorized or measured within a given context.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd383dce881909411a38c6d37bc3a |
completed | March 7, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69abd0ce4dcc8190b17a65abf9bd1bb0 |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd251b48c8190862c7b39ea1bf8ea |
completed | March 7, 2026, 7:22 a.m. |
Created at: March 6, 2026, 9:48 p.m.