Triple
T17355569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belfast West |
E421924
|
entity |
| Predicate | hasTurnoutPattern |
P73416
|
FINISHED |
| Object | varied across elections |
—
|
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: varied across elections | Statement: [Belfast West, hasTurnoutPattern, varied across elections]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTurnoutPattern Context triple: [Belfast West, hasTurnoutPattern, varied across elections]
-
A.
turnout
Indicates the number or proportion of participants who attend or take part in an event or activity.
-
B.
hasFootfallPattern
Indicates a characteristic pattern or sequence of steps, movements, or impacts made by an entity’s feet during locomotion or activity.
-
C.
hasTrafficPattern
Indicates that there is a characteristic or recurring flow of traffic associated with an entity, such as its typical volume, direction, or timing of movement.
-
D.
hasDemographicPattern
Indicates that there is a characteristic distribution or trend of attributes (such as age, gender, income, or ethnicity) within a population or group.
-
E.
turnoutVariesByYear
chosen
Indicates that the level of turnout changes depending on the specific year considered.
- 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_69d889d520008190a26917a95bf1c2ea |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a487bd8819081c6d1e4aa466d6f |
completed | April 19, 2026, 2:13 a.m. |
| PD | Predicate disambiguation | batch_69e3b02662d08190a07d0fb5c04b6f33 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:44 a.m.