Triple
T23690113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1979 Spanish general election |
E585273
|
entity |
| Predicate | electoralSystemForCongress |
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: [1979 Spanish general election, electoralSystemForCongress, proportional representation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electoralSystemForCongress Context triple: [1979 Spanish general election, electoralSystemForCongress, proportional representation]
-
A.
electoralSystemForLegislature
chosen
Indicates the type of electoral system used to choose members of a particular legislature.
-
B.
countryElectoralSystem
Indicates the type of electoral system used by a country to conduct its elections.
-
C.
electoralSystemCurrent
Indicates that the specified electoral system is the one currently in use in a given political or administrative context.
-
D.
electoralSystemContext
Indicates the electoral system or framework within which a political or electoral event, action, or relationship takes place.
-
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_69e249037ce0819088b149608e98f685 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b5c16af08190b2f4d126c60a7e75 |
completed | April 29, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:52 p.m.