Triple
T13161676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jefferson Parish |
E312740
|
entity |
| Predicate | isPartiallySuburban |
P107069
|
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: [Jefferson Parish, isPartiallySuburban, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartiallySuburban Context triple: [Jefferson Parish, isPartiallySuburban, true]
-
A.
isPartiallyUrbanized
chosen
Indicates that an area or region has undergone some degree of urban development but still retains significant non-urban or rural characteristics.
-
B.
isSuburbanCommunity
Indicates that a community is located in a suburban area, typically characterized by residential neighborhoods situated between urban centers and rural regions.
-
C.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
-
D.
isSuburbanResidentialArea
Indicates that a location is primarily a residential neighborhood situated in a suburban (non-urban, non-rural) setting.
-
E.
isInSuburbanArea
Indicates that something is located within a suburban area, typically between urban and rural regions.
- 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_69d806ac3ee081909b2fd27d060aa974 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bbd1d088190b7c69f37fc6eeb64 |
completed | April 10, 2026, 11:46 p.m. |
Created at: April 9, 2026, 9:12 p.m.