Triple
T28082285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Senate of Argentina |
E709713
|
entity |
| Predicate | seatsPerDistrict |
P59176
|
FINISHED |
| Object | 3 senators per province |
—
|
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: 3 senators per province | Statement: [Senate of Argentina, seatsPerDistrict, 3 senators per province]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatsPerDistrict Context triple: [Senate of Argentina, seatsPerDistrict, 3 senators per province]
-
A.
minimumSeatsPerDistrict
Indicates the required minimum number of seats that must be allocated to each district.
-
B.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
C.
electoralRegionSeatCount
chosen
Indicates the number of seats allocated to a given electoral region within a representative body or legislature.
-
D.
regionSeatsCount
Indicates the number of seats allocated or available within a specific region.
-
E.
parliamentarySeats
Indicates the number of seats a party, group, or representative holds in a parliamentary body.
- 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_69ef9b7037f0819095bb90eaccbcaf32 |
completed | April 27, 2026, 5:22 p.m. |
| NER | Named-entity recognition | batch_69f65a6c900881908f18b61273d7bf8d |
completed | May 2, 2026, 8:11 p.m. |
| PD | Predicate disambiguation | batch_69f659ce58408190ba9e007b4810d4d0 |
completed | May 2, 2026, 8:08 p.m. |
Created at: April 27, 2026, 8:52 p.m.