Triple
T9047277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rotor |
E216785
|
entity |
| Predicate | sportOfAssociatedClub |
P48352
|
FINISHED |
| Object | association football |
—
|
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: association football | Statement: [Rotor, sportOfAssociatedClub, association football]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportOfAssociatedClub Context triple: [Rotor, sportOfAssociatedClub, association football]
-
A.
associationFootballClub
Indicates that the subject is an association football (soccer) club, i.e., an organized team entity that plays the sport of association football.
-
B.
associatedWithFootballClub
Indicates that there is a relationship of affiliation or connection between an entity and a football club.
-
C.
sportOfReferencedTeam
chosen
Indicates that the subject is the sport played by, or associated with, the referenced team.
-
D.
associatedClubState
Indicates that there is a relationship between an entity and the state-level club or organization with which it is formally connected or affiliated.
-
E.
sportNumberOfClubs
Indicates the number of clubs or teams an entity is associated with in a sports context.
- 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_69ca83d362e88190ae44b4e4dc194209 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc6b5022c88190ab6b6de3c3830a41 |
completed | April 1, 2026, 12:48 a.m. |
| PD | Predicate disambiguation | batch_69cc5ee566b081909e3cdaf551dbd0ec |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7:09 p.m.