Triple
T12490621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FA Cup 2008–09 with Chelsea |
E298550
|
entity |
| Predicate | trophyNumberForClub |
P66411
|
FINISHED |
| Object | fifth FA Cup title for Chelsea |
—
|
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: fifth FA Cup title for Chelsea | Statement: [FA Cup 2008–09 with Chelsea, trophyNumberForClub, fifth FA Cup title for Chelsea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trophyNumberForClub Context triple: [FA Cup 2008–09 with Chelsea, trophyNumberForClub, fifth FA Cup title for Chelsea]
-
A.
trophyCount
chosen
Indicates the number of trophies associated with a given entity.
-
B.
currentClubNumber
Indicates the jersey or squad number currently assigned to a person at their present club or team.
-
C.
managedTeamToTrophy
Indicates that a person managed a team that went on to win a trophy or championship.
-
D.
sportNumberOfClubs
Indicates the number of clubs or teams an entity is associated with in a sports context.
-
E.
trophyOfficialName
Indicates the official, formally recognized name assigned to a particular trophy.
- 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_69d6ada377208190a36011199a4d8558 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d94e8a706c8190873623eab7db607d |
completed | April 10, 2026, 7:24 p.m. |
| PD | Predicate disambiguation | batch_69d94d41f3cc8190a3331fb9a895306f |
completed | April 10, 2026, 7:19 p.m. |
Created at: April 8, 2026, 9:56 p.m.