Triple
T6637730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France women’s national football team |
E150499
|
entity |
| Predicate | bestUefaWomen’sChampionshipResult |
P71870
|
FINISHED |
| Object | semi-finals |
—
|
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: semi-finals | Statement: [France women’s national football team, bestUefaWomen’sChampionshipResult, semi-finals]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bestUefaWomen’sChampionshipResult Context triple: [France women’s national football team, bestUefaWomen’sChampionshipResult, semi-finals]
-
A.
UEFASuperCupTitles
Indicates the number of UEFA Super Cup titles an entity has won.
-
B.
UEFACupRunnersUp
Indicates that an entity finished as the runner-up (losing finalist) in a UEFA Cup competition.
-
C.
FIFA100Women
Indicates that a person is recognized as one of the top 100 women footballers selected by FIFA.
-
D.
bestConfederationsCupResult
Indicates the highest achievement or best performance an entity has attained in the FIFA Confederations Cup competition.
-
E.
worldCupRunnersUpFinishes
Indicates the number of times an entity has finished as the runner-up in the FIFA World Cup.
- 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_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. |
| PDg | Predicate description generation | batch_69c6c30733908190980f7ffaa5c5527b |
completed | March 27, 2026, 5:48 p.m. |
Created at: March 27, 2026, 1:59 p.m.