Triple
T6637728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France women’s national football team |
E150499
|
entity |
| Predicate | uefaWomen’sChampionshipAppearances |
P18049
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [France women’s national football team, uefaWomen’sChampionshipAppearances, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uefaWomen’sChampionshipAppearances Context triple: [France women’s national football team, uefaWomen’sChampionshipAppearances, 7]
-
A.
EuropeanChampionshipAppearances
chosen
Indicates the number of times an entity has participated in a European Championship tournament.
-
B.
europeanChampionshipAppearance
Indicates that an entity has participated in at least one edition of a European championship competition.
-
C.
uefaNationsLeagueTitles
Indicates the number of UEFA Nations League championship titles an entity (typically a national football team) has won.
-
D.
wonEuropeanChampionship
Indicates that an entity achieved first place or overall victory in a European Championship competition.
-
E.
ConfederationsCupAppearances
Indicates the number of times an entity has participated in the FIFA Confederations Cup tournament.
- 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_69c687f0ceb08190bf40807bfc605fa5 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6c308a08881908501c862b3029321 |
completed | March 27, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69c6ad024860819084b9b535b136ede6 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:59 p.m.