Triple
T1125798
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CONCACAF W Gold Cup |
E24716
|
entity |
| Predicate | numberOfTeamsFirstEdition |
P3770
|
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: [CONCACAF W Gold Cup, numberOfTeamsFirstEdition, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTeamsFirstEdition Context triple: [CONCACAF W Gold Cup, numberOfTeamsFirstEdition, 12]
-
A.
hasNumberOfTeams
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
formerNumberOfTeams
Indicates the number of teams that an entity previously had before a change or reorganization.
-
C.
foundedWithNumberOfTeams
chosen
Indicates the number of teams involved at the time an organization, league, or competition was founded.
-
D.
numberOfTeamsVariesBetween
Indicates that the count of teams involved changes within a specified range or across different instances or conditions.
-
E.
numberOfTeamsVariesByYear
Indicates that the number of teams involved changes depending on the specific year.
- 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_69a4940712c88190aa244f3fc6070a65 |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4bc4bc21881909dcfe628f59f3e8c |
completed | March 1, 2026, 10:23 p.m. |
| PD | Predicate disambiguation | batch_69a4bb4749ac8190b0fbddac2e9b2586 |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:44 p.m.