Triple
T26947214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tamra |
E678678
|
entity |
| Predicate | hasSportsClubsType |
P103892
|
FINISHED |
| Object | football club |
—
|
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: football club | Statement: [Tamra, hasSportsClubsType, football club]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSportsClubsType Context triple: [Tamra, hasSportsClubsType, football club]
-
A.
hasSportsClubs
chosen
Indicates that an entity possesses, hosts, or is associated with one or more sports clubs.
-
B.
hasProfessionalClubs
Indicates that there exists a professional sports or activity club associated with, based in, or belonging to the given entity.
-
C.
associatedClubSport
Indicates that there is a relationship between a club and the sport with which it is connected or aligned.
-
D.
hasSportsVenueType
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
-
E.
hasAthleticTeamType
Indicates that an entity’s athletic team participates in or is classified under a specific type or category of sport or competition.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f707f7959881908f037f0d6b1d0c36 |
completed | May 3, 2026, 8:31 a.m. |
| PD | Predicate disambiguation | batch_69f700fc274c8190a128593dc7c7abd0 |
completed | May 3, 2026, 8:02 a.m. |
Created at: April 27, 2026, 6:22 a.m.