Triple
T32442126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Segunda División Amateur (Uruguay) |
E829042
|
entity |
| Predicate | includesClubsType |
P19215
|
FINISHED |
| Object | amateur football clubs |
—
|
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: amateur football clubs | Statement: [Segunda División Amateur (Uruguay), includesClubsType, amateur football clubs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesClubsType Context triple: [Segunda División Amateur (Uruguay), includesClubsType, amateur football clubs]
-
A.
includesInvitedClubs
Indicates that certain clubs are explicitly included among those invited to participate in a given event or context.
-
B.
refersToClubType
chosen
Indicates that one entity is associated with or designates a particular type or category of club.
-
C.
memberClubsType
Indicates that an entity is associated as a member with clubs of a specified type or category.
-
D.
appliesToClub
Indicates that something (such as a rule, policy, attribute, or action) is relevant or applicable specifically to a particular club.
-
E.
includesClubLevel
Indicates that one entity encompasses or provides access to a specific club-level tier, area, or privileges associated with another entity.
- 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_69f3491d2e5c819092b1c9535beff8ec |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a01d339feac8190a3de56b24db67163 |
completed | May 11, 2026, 1:01 p.m. |
| PD | Predicate disambiguation | batch_6a01d2bc1f408190a04869f95e6941ee |
completed | May 11, 2026, 12:59 p.m. |
Created at: May 1, 2026, 12:55 a.m.