Triple
T4031089
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Athletics |
E83710
|
entity |
| Predicate | hasMemberFederations |
P7638
|
FINISHED |
| Object | more than 200 national federations |
—
|
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: more than 200 national federations | Statement: [World Athletics, hasMemberFederations, more than 200 national federations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMemberFederations Context triple: [World Athletics, hasMemberFederations, more than 200 national federations]
-
A.
hasMemberJurisdictions
Indicates that an administrative or organizational entity includes specific jurisdictions as its constituent members.
-
B.
hasNonRegionalMemberCountries
Indicates that an organization includes member countries that are not part of the primary geographic region with which the organization is associated.
-
C.
memberStatesAreMemberOf
Indicates that certain states belong to or hold membership in a particular organization, group, or union.
-
D.
hasNumberOfMemberInstitutions
Indicates the quantitative count of member institutions associated with a given entity.
-
E.
hasMembers
chosen
Indicates that a group, organization, or collection includes certain entities as its members.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb0dbb8481909ff2ee49dadcd1dc |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fe440c819093a7fa22c4ff3f1a |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.