Triple
T28734464
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian regional elections |
E730756
|
entity |
| Predicate | turnoutType |
P165272
|
FINISHED |
| Object | compulsory voting |
—
|
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: compulsory voting | Statement: [Belgian regional elections, turnoutType, compulsory voting]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: turnoutType Context triple: [Belgian regional elections, turnoutType, compulsory voting]
-
A.
turnout
Indicates the number or proportion of participants who attend or take part in an event or activity.
-
B.
turnType
Indicates the specific kind or category of turn being made in a movement or path (e.g., left turn, right turn, U-turn).
-
C.
turnoverType
Indicates the specific category or nature of a turnover event, such as how or why control of an asset, position, or role changes from one party to another.
-
D.
turnsIn
Indicates that an entity submits or hands over something, typically work or an item, to another party or authority.
-
E.
ovalType
Indicates that one entity is classified as having an oval shape or belonging to an oval-shaped type.
- F. None of above. chosen
Provenance (4 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_69f043eae0908190b28ce314686247d7 |
completed | April 28, 2026, 5:21 a.m. |
| NER | Named-entity recognition | batch_69f6576a87648190a48a42a50d9925c6 |
completed | May 2, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69f651ac855481908e30c3b345d31356 |
completed | May 2, 2026, 7:34 p.m. |
| PDg | Predicate description generation | batch_69f6562ef4e4819082ce6abd41b74dc5 |
completed | May 2, 2026, 7:53 p.m. |
Created at: April 28, 2026, 6 a.m.