Triple
T1345009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia State Senate |
E28549
|
entity |
| Predicate | representationBasis |
P14358
|
FINISHED |
| Object | single-member districts |
—
|
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: single-member districts | Statement: [Georgia State Senate, representationBasis, single-member districts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representationBasis Context triple: [Georgia State Senate, representationBasis, single-member districts]
-
A.
representationType
Indicates the specific form or mode in which something is represented or expressed (e.g., as a symbol, image, model, or description).
-
B.
representation
chosen
Indicates that one entity stands in for, symbolizes, or depicts another entity in some context.
-
C.
returnBasis
Indicates the basis, method, or terms under which something is returned (e.g., goods, funds, or data) from one party or context to another.
-
D.
reducedRepresentationOf
Indicates that one entity is a simplified, compressed, or lower-detail version of another entity while preserving its essential information or structure.
-
E.
encodingBasisFor
Indicates that one encoding scheme serves as the foundational or reference basis for defining or interpreting another encoding.
- 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.