Triple
T24404086
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senedd electoral regions of Wales |
E615258
|
entity |
| Predicate | numberOfMembersPerRegion |
P51092
|
FINISHED |
| Object | 4 additional members |
—
|
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: 4 additional members | Statement: [Senedd electoral regions of Wales, numberOfMembersPerRegion, 4 additional members]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMembersPerRegion Context triple: [Senedd electoral regions of Wales, numberOfMembersPerRegion, 4 additional members]
-
A.
numberOfRegionalMembers
chosen
Indicates the quantity of members associated with or belonging to a specific region within a given context.
-
B.
numberOfRegions
Indicates the total count of distinct regions associated with or contained within a given entity.
-
C.
nativeRegionOfMembers
Indicates the geographic region from which the members of a group or organization originally come.
-
D.
numberOfDistrictMembers
Indicates the relationship that specifies how many members are associated with a given district.
-
E.
memberAssociationCount
Indicates the number of associations or group memberships linked to a given member.
- 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_69e2d7e780bc81908049c779e697a7f6 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294dcf7f4819094d2a3be163a5822 |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:05 a.m.