Triple
T11031074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rugby Africa |
E260756
|
entity |
| Predicate | memberUnionCount |
P21800
|
FINISHED |
| Object | more than 30 national rugby unions |
—
|
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 30 national rugby unions | Statement: [Rugby Africa, memberUnionCount, more than 30 national rugby unions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberUnionCount Context triple: [Rugby Africa, memberUnionCount, more than 30 national rugby unions]
-
A.
memberAssociationCount
Indicates the number of associations or group memberships linked to a given member.
-
B.
numberOfMemberOrganizations
chosen
Indicates the total count of organizations that are members of a given group, association, or umbrella entity.
-
C.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
D.
numberOfMembersDeterminedBy
Indicates that the quantity of members in one entity is defined or constrained by another entity or factor.
-
E.
numberOfRegionalMembers
Indicates the quantity of members associated with or belonging to a specific region within a given context.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797d3bba08190b5134e520225baca |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d7440087ac8190aef2e6f6b13b2635 |
completed | April 9, 2026, 6:15 a.m. |
Created at: April 8, 2026, 9:25 p.m.