Triple
T24036027
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Champions Indoor Football |
E595234
|
entity |
| Predicate | typicalTeamCountRange |
P18041
|
FINISHED |
| Object | 8–16 teams |
—
|
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: 8–16 teams | Statement: [Champions Indoor Football, typicalTeamCountRange, 8–16 teams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalTeamCountRange Context triple: [Champions Indoor Football, typicalTeamCountRange, 8–16 teams]
-
A.
typicalTeamSize
Indicates the usual or most common number of members that make up a given team.
-
B.
numberOfTeamsVariesBetween
chosen
Indicates that the count of teams involved changes within a specified range or across different instances or conditions.
-
C.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
D.
teamCountType
Indicates how the number of teams is categorized or measured within a given context.
-
E.
typicalNumberOfCWSTeams
Indicates the usual or standard number of CWS teams associated with or involved in a given context or entity.
- 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_69e288bf45f08190a1b6ed8cd0b9e86b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d8d43884819093e9207a99ae2a70 |
completed | April 29, 2026, 10:09 a.m. |
| PD | Predicate disambiguation | batch_69f1764345388190a3102b62ddb729b4 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 9:56 p.m.