Triple
T469340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Georgia State Route 54 |
E8518
|
entity |
| Predicate | traversesAreaType |
P6822
|
FINISHED |
| Object | urban areas |
—
|
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: urban areas | Statement: [Georgia State Route 54, traversesAreaType, urban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traversesAreaType Context triple: [Georgia State Route 54, traversesAreaType, urban areas]
-
A.
hasAreaType
chosen
Indicates that an entity is associated with a specific kind or classification of area (e.g., urban, rural, coastal).
-
B.
crossingType
Indicates the specific kind or category of crossing (e.g., how or where one thing passes over, through, or across another).
-
C.
regionType
Indicates the classification or category of a region, specifying what kind of region it is (e.g., administrative, geographic, or functional).
-
D.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
-
E.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
- 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_69a2e7f3aeb48190a19453e3a043f486 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2efee0ea0819099d87f3727c03bc7 |
completed | Feb. 28, 2026, 1:38 p.m. |
| PD | Predicate disambiguation | batch_69a2edebb3988190907992a584b4e260 |
completed | Feb. 28, 2026, 1:30 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.