Triple
T10500245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States federal electoral districts |
E247652
|
entity |
| Predicate | minimumDistrictsPerState |
P59784
|
FINISHED |
| Object | 1 |
—
|
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: 1 | Statement: [United States federal electoral districts, minimumDistrictsPerState, 1]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: minimumDistrictsPerState Context triple: [United States federal electoral districts, minimumDistrictsPerState, 1]
-
A.
minimumSeatsPerState
chosen
Indicates the smallest number of seats that must be allocated to each state in a representative body or legislative apportionment.
-
B.
numberOfDistricts
Indicates the total count of districts associated with a given entity or area.
-
C.
maximumSeatsPerState
Indicates the upper limit on the number of seats that any single state is allowed to have.
-
D.
eachDistrictElects
Indicates that every electoral district selects or chooses its own representative or set of representatives.
-
E.
numberOfSenateDistricts
Indicates the total count of senate districts associated with a given entity or jurisdiction.
- 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5098ef57c8190a9803c2c1736d299 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8e24ac8190912c9f11b8bd3084 |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:25 p.m.