Triple
T11631556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2017–18 UEFA Champions League |
E276409
|
entity |
| Predicate | titleConsecutiveNumberForChampion |
P87395
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [2017–18 UEFA Champions League, titleConsecutiveNumberForChampion, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleConsecutiveNumberForChampion Context triple: [2017–18 UEFA Champions League, titleConsecutiveNumberForChampion, 3]
-
A.
consecutiveTitleNumberForChampion
chosen
Indicates that the associated number represents how many titles a champion has won consecutively up to that point.
-
B.
consecutiveTitlesForChampion
Indicates that a champion has won multiple titles in succession without interruption.
-
C.
championConsecutiveTitlesStart
Indicates the point in time or event at which an entity begins a streak of winning championship titles in consecutive editions of a competition.
-
D.
championCityTitleNumber
Indicates the ordinal number of championship titles that a particular city has won or holds in a given competition or league.
-
E.
consecutiveTitleNumber
Indicates that one entity’s title number immediately follows another’s in a sequential ordering.
- 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_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. |
Created at: April 8, 2026, 9:39 p.m.