Triple
T22187582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Italy women's national football team |
E548334
|
entity |
| Predicate | bestResultUefaWomensChampionship |
P71870
|
FINISHED |
| Object | runners-up |
—
|
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: runners-up | Statement: [Italy women's national football team, bestResultUefaWomensChampionship, runners-up]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestResultUefaWomensChampionship Context triple: [Italy women's national football team, bestResultUefaWomensChampionship, runners-up]
-
A.
bestUefaWomen’sChampionshipResult
chosen
Indicates the highest level of success an entity has achieved in the UEFA Women's Championship competition.
-
B.
FIFAWomen'sWorldCupAllTimeTopScorer
Indicates that the subject holds the record for scoring the most goals in the history of the FIFA Women's World Cup.
-
C.
bestUEFACupPerformance
Indicates the highest level or furthest stage an entity has ever reached in UEFA Cup competition.
-
D.
wonEuropeanChampionship
Indicates that an entity achieved first place or overall victory in a European Championship competition.
-
E.
UEFASuperCupTitles
Indicates the number of UEFA Super Cup titles 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aaa32288190830f6dfc626fb26a |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:35 p.m.