Triple
T9320269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Owings, Maryland |
E224234
|
entity |
| Predicate | suburbanRuralCharacter |
P9847
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Owings, Maryland, suburbanRuralCharacter, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanRuralCharacter Context triple: [Owings, Maryland, suburbanRuralCharacter, true]
-
A.
semiRuralCharacter
Indicates that a place or area has characteristics intermediate between rural and urban, combining elements of both environments.
-
B.
hasSuburbanCharacter
chosen
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
C.
hasRuralZoningCharacter
Indicates that a property or area possesses zoning attributes and regulations typical of rural land use.
-
D.
isPredominantlyRural
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
E.
hasRuralLandscapeType
Indicates that an entity is associated with or characterized by a specific type of rural landscape.
- 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_69ca8426d48481909596360f7791c7dd |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd358dcb4c81909e00bfb58a6dda3f |
completed | April 1, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69cc7a61e9a4819096eb014f3791ef2e |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:38 p.m.