Triple
T10237266
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greek Cup |
E243495
|
entity |
| Predicate | hasProfessionalClubs |
P92908
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Greek Cup, hasProfessionalClubs, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalClubs Context triple: [Greek Cup, hasProfessionalClubs, yes]
-
A.
sportNumberOfClubs
Indicates the number of clubs or teams an entity is associated with in a sports context.
-
B.
hasProfessionalLeague
Indicates that an entity is associated with or participates in a recognized professional sports league.
-
C.
hasManagedClub
Indicates that a person has held a managerial role for a particular club.
-
D.
eligibleClubs
Indicates that certain clubs meet the required criteria or conditions to qualify for a specified status, activity, or benefit.
-
E.
hasProfessionalPlayers
Indicates that an entity is associated with or includes individuals who participate in a profession at a professional level.
- 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_69d381b0f97c819085c9b45799a5fb7c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d23b620c8190b8a72d0eb0d16b93 |
completed | April 7, 2026, 9:45 a.m. |
| PD | Predicate disambiguation | batch_69d4d1e9798c8190b437d53d48554ba1 |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d23a9c4c8190abece9e52879c479 |
completed | April 7, 2026, 9:45 a.m. |
Created at: April 6, 2026, 11:22 a.m.