Triple
T24809633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2011 National Assembly for Wales election |
E620747
|
entity |
| Predicate | electoralRegionCount |
P2355
|
FINISHED |
| Object | 5 |
—
|
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: 5 | Statement: [2011 National Assembly for Wales election, electoralRegionCount, 5]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electoralRegionCount Context triple: [2011 National Assembly for Wales election, electoralRegionCount, 5]
-
A.
electoralRegionSeatCount
Indicates the number of seats allocated to a given electoral region within a representative body or legislature.
-
B.
numberOfRegions
chosen
Indicates the total count of distinct regions associated with or contained within a given entity.
-
C.
numberOfElectorates
Indicates the total count of electoral districts or constituencies associated with a given entity.
-
D.
numberOfRegionalCouncils
Indicates the total count of regional councils associated with a given entity.
-
E.
hasNumberOfConstituencies
Indicates the specific count of constituencies associated with an 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_69e2fabf26bc8190b191faac8f67065b |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f55e519978819087a1676564a74630 |
completed | May 2, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69f4a0edd10c81908a052ab864d57c54 |
completed | May 1, 2026, 12:47 p.m. |
Created at: April 18, 2026, 4:50 a.m.