Triple
T24167286
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Australia women's national soccer team |
E599023
|
entity |
| Predicate | wonAFCWomensAsianCup |
P57825
|
FINISHED |
| Object | 2010 |
—
|
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: 2010 | Statement: [Australia women's national soccer team, wonAFCWomensAsianCup, 2010]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wonAFCWomensAsianCup Context triple: [Australia women's national soccer team, wonAFCWomensAsianCup, 2010]
-
A.
wonAsianCupWinnersCup
Indicates that one entity (typically a sports team or club) has won the Asian Cup Winners' Cup competition.
-
B.
asiaCupWinner
chosen
Indicates that one entity is the champion or winning team of the Asia Cup tournament in a given edition or year.
-
C.
wonFAcup
Indicates that the subject has won the FA Cup football competition.
-
D.
wonAFCChampionsLeague
Indicates that the subject has won the AFC Champions League football competition.
-
E.
asiaCupBestPerformance
Indicates the best result or highest achievement an entity has attained in the Asia Cup competition.
- 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_69e288cbd62881909de32ca64a70c17b |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27c9ddfcc819096697a844b300cce |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c42f942c8190b103ff29a60fef34 |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:33 p.m.