Triple
T28211654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Système pratique et raisonné de représentation proportionnelle |
E711183
|
entity |
| Predicate | citationSubject |
P164130
|
FINISHED |
| Object | comparative electoral systems literature |
—
|
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: comparative electoral systems literature | Statement: [Système pratique et raisonné de représentation proportionnelle, citationSubject, comparative electoral systems literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citationSubject Context triple: [Système pratique et raisonné de représentation proportionnelle, citationSubject, comparative electoral systems literature]
-
A.
citationSubject
chosen
Indicates that one entity is the subject or topic being cited or referenced by another entity.
-
B.
citationOf
Indicates that one entity cites, references, or formally acknowledges another entity as a source.
-
C.
citationType
Indicates the specific kind or category of citation relationship that one entity has to another (e.g., reference, quotation, acknowledgment).
-
D.
citationBy
Indicates that one work is cited or referenced by another work.
-
E.
citationIn
Indicates that one work cites, references, or otherwise acknowledges another work as a source.
- 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_69efb51cb5288190818c1f63a266af11 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f64312f0f081909d8cb61e9cd52b16 |
completed | May 2, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:39 p.m.