Triple
T2430106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boundary Commission for Wales |
E52821
|
entity |
| Predicate | workPeriodicity |
P7407
|
FINISHED |
| Object | periodic general reviews of constituencies |
—
|
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: periodic general reviews of constituencies | Statement: [Boundary Commission for Wales, workPeriodicity, periodic general reviews of constituencies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workPeriodicity Context triple: [Boundary Commission for Wales, workPeriodicity, periodic general reviews of constituencies]
-
A.
workPeriod
Indicates the span of time during which an entity is engaged in a particular work or employment activity.
-
B.
workSettingPeriod
Indicates the time period during which a particular work setting or employment context is in effect.
-
C.
workPattern
Indicates the typical schedule, structure, or arrangement according to which an entity performs its work or duties.
-
D.
workLength
Indicates the duration or length of time associated with a particular work or task.
-
E.
tienePeriodicidad
chosen
Indicates that something occurs, recurs, or is scheduled with a specific regular frequency or periodic pattern.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcc74a5108190a3a9631b0cc1a127 |
completed | March 7, 2026, 6:57 a.m. |
| PD | Predicate disambiguation | batch_69abc5aa1b60819081b87f7985c6cff3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 6, 2026, 9:43 p.m.