Triple
T28258658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Argentina women's national football team |
E712520
|
entity |
| Predicate | copaAmericaFemeninaTitles |
P40866
|
FINISHED |
| Object | 2006 |
—
|
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: 2006 | Statement: [Argentina women's national football team, copaAmericaFemeninaTitles, 2006]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: copaAmericaFemeninaTitles Context triple: [Argentina women's national football team, copaAmericaFemeninaTitles, 2006]
-
A.
sharedMostCopaAmericaTitlesWith
Indicates that two entities hold the highest and equal number of Copa América titles compared to all other entities.
-
B.
FIFAWomensWorldCupAppearances
Indicates the number of times an entity has participated in the FIFA Women's World Cup tournament.
-
C.
teamNumberOfTitlesWithUSWNT
Indicates the number of titles a team has won in competitions involving the United States Women's National Team (USWNT).
-
D.
copaAmericaTitleYear
chosen
Indicates the specific year in which a given Copa América title was won.
-
E.
ConfederationsCupTitles
Indicates the number of FIFA Confederations Cup championships an entity has won.
- 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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f643f68c2c8190b44dd5a13238288a |
completed | May 2, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 11:10 p.m.