Triple
T11631557
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017–18 UEFA Champions League |
E276409
|
entity |
| Predicate | titleTotalNumberForChampion |
P100670
|
FINISHED |
| Object | 13 |
—
|
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: 13 | Statement: [2017–18 UEFA Champions League, titleTotalNumberForChampion, 13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleTotalNumberForChampion Context triple: [2017–18 UEFA Champions League, titleTotalNumberForChampion, 13]
-
A.
leagueChampionFranchisePennantCount
Indicates the number of league championship pennants won by a given franchise.
-
B.
championRank
Indicates the relative level or position of an entity within a competitive ranking or championship hierarchy.
-
C.
championTotalWinsIncludingPostseason
Indicates the total number of games a champion has won in a season, counting both regular season and postseason victories.
-
D.
leagueOfChampion
Indicates that an entity is the league or competition in which a given champion or titleholder competes or holds their status.
-
E.
championRegularSeasonWins
Indicates that an entity is the champion based on having the highest number of regular season wins.
- 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_69d6aafa51148190ab84940694c00235 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a25aa9188190ab13d79139f37e7e |
completed | April 10, 2026, 7:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd94bdc819091fa2ed33eb31624 |
completed | April 10, 2026, 2:18 a.m. |
| PDg | Predicate description generation | batch_69d87f2e67108190ac36bf47aac12fa8 |
completed | April 10, 2026, 4:40 a.m. |
Created at: April 8, 2026, 9:39 p.m.