Triple
T38561493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1996 UEFA Champions League Final |
E928085
|
entity |
| Predicate | JuventusTitleCountEuropeanCupChampionsLeague |
P15090
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [1996 UEFA Champions League Final, JuventusTitleCountEuropeanCupChampionsLeague, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: JuventusTitleCountEuropeanCupChampionsLeague Context triple: [1996 UEFA Champions League Final, JuventusTitleCountEuropeanCupChampionsLeague, 2]
-
A.
JuventusTitleCount
Indicates the number of titles that Juventus has won.
-
B.
UEFAChampionsLeagueTitles
chosen
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
C.
CAFChampionsLeagueTitles
Indicates the number of CAF Champions League titles an entity has won.
-
D.
numberOfTropheeDesChampionsTitles
Indicates the number of Trophée des Champions titles that an entity has won.
-
E.
juventusConsecutiveFinalsNumber
Indicates the number of consecutive finals that Juventus has reached or participated in within a given competition or context.
- 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_69f76eb8d1808190a588af29d8b266d6 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fce28d6c3081908bf76f5db63ecf68 |
completed | May 7, 2026, 7:05 p.m. |
| PD | Predicate disambiguation | batch_69fce12d2f08819082134b5eb3db6a24 |
completed | May 7, 2026, 6:59 p.m. |
Created at: May 3, 2026, 4:32 p.m.