Triple
T18712192
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Carolina's 1st congressional district |
E457543
|
entity |
| Predicate | predominantAreaType |
P1828
|
FINISHED |
| Object | rural |
—
|
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: rural | Statement: [North Carolina's 1st congressional district, predominantAreaType, rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predominantAreaType Context triple: [North Carolina's 1st congressional district, predominantAreaType, rural]
-
A.
typicalRegionType
Indicates that a region is of a characteristic or commonly occurring type for a given context or entity.
-
B.
urbanDistrictType
Indicates the classification of an urban district according to its specific type or category within an administrative or planning system.
-
C.
suburbanAreasDominatedBy
Indicates that one suburban area is predominantly controlled, influenced, or characterized by another entity (such as a group, activity, or demographic).
-
D.
urbanAreaType
Indicates the classification of an area based on its urban characteristics or development type (e.g., city, town, suburb, metropolitan region).
-
E.
regionType
chosen
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
- 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5671c53988190bfc132c853cebd02 |
completed | April 19, 2026, 11:37 p.m. |
| PD | Predicate disambiguation | batch_69e478e0889c8190a118d67b200ce8ef |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:50 a.m.