Triple
T1345010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia State Senate |
E28549
|
entity |
| Predicate | districtApportionment |
P11387
|
FINISHED |
| Object | based on population |
—
|
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: based on population | Statement: [Georgia State Senate, districtApportionment, based on population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: districtApportionment Context triple: [Georgia State Senate, districtApportionment, based on population]
-
A.
apportionedBy
Indicates that something is divided or allocated among parts or recipients according to a specified agent, rule, or method.
-
B.
apportionmentUnit
chosen
Indicates a relationship where something (such as a resource, cost, or quantity) is divided or allocated according to a specified unit or basis of apportionment.
-
C.
congressionalDistrict
Indicates that one entity is a congressional district that politically represents or geographically contains the other entity.
-
D.
numberOfRepresentatives
Indicates the quantity of representatives associated with a given entity or unit.
-
E.
seatOfElector
Indicates the location or jurisdiction that serves as the official base or constituency of a given elector.
- 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_69a49854eb3481908c7d56b2e449a290 |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c23d696c8190bb688274280cb680 |
completed | March 1, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69a4bef3e8fc8190ac9a1ba9b5879483 |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:56 p.m.