Triple
T31548331
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | City of Manchester |
E804925
|
entity |
| Predicate | hasProfessionalFootballClub |
P92908
|
FINISHED |
| Object | Manchester City F.C. |
—
|
NE NERFINISHED |
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: Manchester City F.C. | Statement: [City of Manchester, hasProfessionalFootballClub, Manchester City F.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalFootballClub Context triple: [City of Manchester, hasProfessionalFootballClub, Manchester City F.C.]
-
A.
hasFootballClubReference
Indicates that one entity includes or maintains a reference to a football club entity.
-
B.
hasSportsClubs
Indicates that an entity possesses, hosts, or is associated with one or more sports clubs.
-
C.
associationFootballClub
Indicates that the subject is an association football (soccer) club, i.e., an organized team entity that plays the sport of association football.
-
D.
hasProfessionalClubs
chosen
Indicates that there exists a professional sports or activity club associated with, based in, or belonging to the given entity.
-
E.
hasFootballTrainingCentre
Indicates that an entity possesses or hosts a facility specifically designated for football training.
- 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_69f348d11a048190a65eb8384a3754ac |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a007241df8081909dbad651fda82aa7 |
completed | May 10, 2026, 11:55 a.m. |
| PD | Predicate disambiguation | batch_6a0071e77ed081908cd618da8977d878 |
completed | May 10, 2026, 11:54 a.m. |
Created at: April 30, 2026, 10:09 p.m.