Triple
T33581680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Route 1 in North Carolina |
E860163
|
entity |
| Predicate | hasRuralHighwaySection |
P143998
|
FINISHED |
| Object | Southern Pines to South Carolina line |
—
|
NE NERFINISHED |
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: Southern Pines to South Carolina line | Statement: [U.S. Route 1 in North Carolina, hasRuralHighwaySection, Southern Pines to South Carolina line]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRuralHighwaySection Context triple: [U.S. Route 1 in North Carolina, hasRuralHighwaySection, Southern Pines to South Carolina line]
-
A.
isRuralHighway
Indicates that a given highway is classified as being located in or primarily serving a rural area.
-
B.
hasRuralSection
chosen
Indicates that an entity includes, contains, or is associated with a portion or segment located in a rural area.
-
C.
hasExpresswaySection
Indicates that an entity includes, contains, or is associated with a specific section or segment of an expressway.
-
D.
hasRoadway
Indicates that one location or area is connected to another by a road or roadway infrastructure.
-
E.
hasMajorHighway
Indicates that a location or area is served by or directly connected to a major highway route.
- 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_69f3497d37848190afcbb5ef3f5c7376 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f73223675481908c1bc3208c0f5284 |
completed | May 3, 2026, 11:31 a.m. |
| PD | Predicate disambiguation | batch_69f7317690108190b3aae2cd2e1d069e |
completed | May 3, 2026, 11:28 a.m. |
Created at: May 1, 2026, 1:40 a.m.