Triple
T2507696
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France national football team |
E52622
|
entity |
| Predicate | uefaEuropeanChampionshipRunnersUpYear |
P13986
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [France national football team, uefaEuropeanChampionshipRunnersUpYear, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uefaEuropeanChampionshipRunnersUpYear Context triple: [France national football team, uefaEuropeanChampionshipRunnersUpYear, 2016]
-
A.
EuropeanChampionshipRunnersUp
chosen
Indicates that an entity finished in second place (as runners-up) in a European Championship competition.
-
B.
UEFAChampionsLeagueRunnersUp
Indicates that an entity finished in second place (as the losing finalist) in a given season of the UEFA Champions League.
-
C.
EuropeanChampionshipRunnerUpIn
Indicates that an entity finished in second place in a specified European Championship competition or edition.
-
D.
UEFACupRunnersUp
Indicates that an entity finished as the runner-up (losing finalist) in a UEFA Cup competition.
-
E.
wonUEFAEuropaConferenceLeagueYear
Indicates that the subject won the UEFA Europa Conference League in the specified year.
- 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_69ab4958e76481908a235377dd921c9e |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd65d6a988190aaaac8e98540a14f |
completed | March 7, 2026, 7:40 a.m. |
| PD | Predicate disambiguation | batch_69abd0bd996c8190ba8b9d6e4333b8d4 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.