Triple
T31436406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 FA Cup Final |
E801943
|
entity |
| Predicate | winningClubTrophyCountFA Cup |
P171870
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [2011 FA Cup Final, winningClubTrophyCountFA Cup, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: winningClubTrophyCountFA Cup Context triple: [2011 FA Cup Final, winningClubTrophyCountFA Cup, 5]
-
A.
numberOfFACupWinsWithClub
Indicates the number of FA Cup titles an entity has won while associated with a specific club.
-
B.
LeagueCupTitles
Indicates the number of league cup championships an entity has won.
-
C.
FA CupRoundsWon
Indicates the number of rounds a team has successfully progressed through (won) in the FA Cup competition.
-
D.
NewcastleUnitedPreviousFAcupWins
Indicates that the subject (Newcastle United) has previously won the FA Cup a certain number of times or in certain years.
-
E.
numberOfTropheeDesChampionsTitles
Indicates the number of Trophée des Champions titles that an entity has won.
- 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_69f348c475348190bf579ca858eec77c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a5f71b2c8190aade8a83f465be0c |
completed | May 3, 2026, 1:33 a.m. |
| PD | Predicate disambiguation | batch_69f69fe66df08190958558d63ee623d9 |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a5f656ec81909e02b0b873303adf |
completed | May 3, 2026, 1:33 a.m. |
Created at: April 30, 2026, 9:02 p.m.