Triple
T30323327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2021 Copa América |
E771263
|
entity |
| Predicate | winnerTitleCountForArgentina |
P179940
|
FINISHED |
| Object | 15 |
—
|
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: 15 | Statement: [2021 Copa América, winnerTitleCountForArgentina, 15]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winnerTitleCountForArgentina Context triple: [2021 Copa América, winnerTitleCountForArgentina, 15]
-
A.
numberOfWorldCupWins
Indicates how many times an entity has won the FIFA World Cup tournament.
-
B.
WorldCupVictories
Indicates the number of times an entity has won the FIFA World Cup tournament.
-
C.
WorldCupWins
Indicates the number of times an entity (typically a national team) has won the FIFA World Cup tournament.
-
D.
sharedMostCopaAmericaTitlesWith
Indicates that two entities hold the highest and equal number of Copa América titles compared to all other entities.
-
E.
pointsScorerForArgentina
Indicates that one entity is the player who scored points for the Argentina team in a game or competition.
- 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_69f22489ee8481909344649bfbb92e83 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f72921cf2c8190909bb53f78bcc890 |
completed | May 3, 2026, 10:53 a.m. |
| PD | Predicate disambiguation | batch_69f7283d8cec8190b524c144948bc4ec |
completed | May 3, 2026, 10:49 a.m. |
| PDg | Predicate description generation | batch_69f72920c6208190aa4aba6cb6193109 |
completed | May 3, 2026, 10:53 a.m. |
Created at: April 29, 2026, 7:52 p.m.