Triple
T14279029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2016 UEFA Champions League Final |
E353992
|
entity |
| Predicate | realMadridChampionsLeagueTitlesTotalAfterMatch |
P113566
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [2016 UEFA Champions League Final, realMadridChampionsLeagueTitlesTotalAfterMatch, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: realMadridChampionsLeagueTitlesTotalAfterMatch Context triple: [2016 UEFA Champions League Final, realMadridChampionsLeagueTitlesTotalAfterMatch, 11]
-
A.
ACMilanEuropeanCupTitlesAfterMatch
Indicates the number of European Cup titles AC Milan has won as of (or following) a specific match.
-
B.
leagueTitlesWonWithRealMadrid
Indicates the number of league titles an individual has won while playing for or managing Real Madrid.
-
C.
CopaDelReyTitles
Indicates the number of Copa del Rey championship titles an entity has won.
-
D.
goalsByRealMadrid
Indicates the number of goals that were scored by Real Madrid.
-
E.
wonCopaDelRey
Indicates that one entity achieved victory in the Copa del Rey competition over another entity or in a specific edition of the tournament.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6585270c8190a717127b2f5dab3b |
completed | April 14, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:10 a.m.