Triple
T17723197
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Government of Paraguay |
E442393
|
entity |
| Predicate | legislativeElectionSystem |
P39112
|
FINISHED |
| Object | proportional representation |
—
|
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: proportional representation | Statement: [Government of Paraguay, legislativeElectionSystem, proportional representation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legislativeElectionSystem Context triple: [Government of Paraguay, legislativeElectionSystem, proportional representation]
-
A.
electoralSystemForLegislature
chosen
Indicates the type of electoral system used to choose members of a particular legislature.
-
B.
electoralSystemCurrent
Indicates that the specified electoral system is the one currently in use in a given political or administrative context.
-
C.
electoralSystemContext
Indicates the electoral system or framework within which a political or electoral event, action, or relationship takes place.
-
D.
electionMethod
Indicates the process or system used to select a candidate or make a decision in an election.
-
E.
electoralSystemConcerned
Indicates that something is related to, affected by, or focused on a particular electoral system.
- 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_69d8b9ec79688190b86bdcef85a7b3aa |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47487b4988190b14237a4e6376e9a |
completed | April 19, 2026, 6:21 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:07 a.m.