Triple
T34901092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Feliciana Parish |
E1006588
|
entity |
| Predicate | isMostlyNonUrban |
P47416
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [East Feliciana Parish, isMostlyNonUrban, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isMostlyNonUrban Context triple: [East Feliciana Parish, isMostlyNonUrban, yes]
-
A.
isLessUrbanizedThan
Indicates that one place has a lower degree of urban development or urban characteristics compared to another place.
-
B.
isPredominantlyRural
chosen
Indicates that a place or region is characterized mainly by rural features, such as low population density and extensive non-urban land use.
-
C.
isPartiallyUrbanized
Indicates that an area or region has undergone some degree of urban development but still retains significant non-urban or rural characteristics.
-
D.
isRuralCity
Indicates that a city is characterized by rural features or is located within a predominantly rural area.
-
E.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
- 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78710282c81909146dc0be91e983f |
completed | May 3, 2026, 5:34 p.m. |
| PD | Predicate disambiguation | batch_69f784162134819098413482ef52042f |
completed | May 3, 2026, 5:21 p.m. |
Created at: May 3, 2026, 4 p.m.