Triple
T12198772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Salisbury (UK Parliament constituency) |
E290657
|
entity |
| Predicate | electsHowOften |
P1678
|
FINISHED |
| Object | at least every five years |
—
|
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: at least every five years | Statement: [Salisbury (UK Parliament constituency), electsHowOften, at least every five years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electsHowOften Context triple: [Salisbury (UK Parliament constituency), electsHowOften, at least every five years]
-
A.
electsRepresentativeEvery
Indicates that one entity periodically chooses or votes to select another entity to serve as its representative.
-
B.
electsAt
Indicates that an election or selection of someone or something to a position, role, or office occurs at a specific time or in a specific context.
-
C.
legislativePeriodicity
chosen
Indicates how frequently a legislative body or process recurs or is scheduled to occur over time.
-
D.
electsInEvenYears
Indicates that the election or selection of an entity occurs specifically in calendar years that are even numbers.
-
E.
isUsuallyElectedFor
Indicates that an entity typically attains a position, role, or office through an election process.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d938cd2edc8190b1971349dbc0dee0 |
completed | April 10, 2026, 5:52 p.m. |
| PD | Predicate disambiguation | batch_69d91c38321c819080d500d0d64a04f6 |
completed | April 10, 2026, 3:50 p.m. |
Created at: April 8, 2026, 9:50 p.m.