Triple
T11803509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UEFA Champions League final 1999-2000 |
E280685
|
entity |
| Predicate | realMadridTitleCountEuropeanCupChampionsLeague |
P15090
|
FINISHED |
| Object | 8 |
—
|
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: 8 | Statement: [UEFA Champions League final 1999-2000, realMadridTitleCountEuropeanCupChampionsLeague, 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realMadridTitleCountEuropeanCupChampionsLeague Context triple: [UEFA Champions League final 1999-2000, realMadridTitleCountEuropeanCupChampionsLeague, 8]
-
A.
leagueTitlesWonWithRealMadrid
Indicates the number of league titles an individual has won while playing for or managing Real Madrid.
-
B.
UEFAChampionsLeagueTitles
chosen
Indicates the number of UEFA Champions League titles an entity (typically a football club) has won.
-
C.
seasonNumberAsChampionsLeague
Indicates the specific season number in which an entity participated in or was associated with the Champions League.
-
D.
CopaDelReyTitles
Indicates the number of Copa del Rey championship titles an entity has won.
-
E.
numberOfUEFAEuropaConferenceLeagueTitles
Indicates the number of UEFA Europa Conference League titles that 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_69d6ab26aae88190b2489efcb2a24234 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a658f918819092c2db05fe2ab0ce |
completed | April 10, 2026, 7:27 a.m. |
| PD | Predicate disambiguation | batch_69d8a24e9a088190aff7932d1ff93dbf |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:42 p.m.