Triple
T15299221
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | International Orienteering Federation |
E365739
|
entity |
| Predicate | hasNumberOfMemberFederations |
P21800
|
FINISHED |
| Object | more than 70 |
—
|
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 70 | Statement: [International Orienteering Federation, hasNumberOfMemberFederations, more than 70]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfMemberFederations Context triple: [International Orienteering Federation, hasNumberOfMemberFederations, more than 70]
-
A.
hasNumberOfMemberInstitutions
Indicates the quantitative count of member institutions associated with a given entity.
-
B.
numberOfRegionalMembers
Indicates the quantity of members associated with or belonging to a specific region within a given context.
-
C.
hasMembersPerState
Indicates a relationship that specifies how many members are associated with each state.
-
D.
hasMemberJurisdictions
Indicates that an administrative or organizational entity includes specific jurisdictions as its constituent members.
-
E.
numberOfMemberOrganizations
chosen
Indicates the total count of organizations that are members of a given group, association, or umbrella 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03686bfb8819080ba0caae652170a |
completed | April 16, 2026, 1:08 a.m. |
| PD | Predicate disambiguation | batch_69deca935e2c8190b640987ddfc542b9 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:15 a.m.