Triple
T21220904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AL-07 |
E522961
|
entity |
| Predicate | isUrbanRuralMixed |
P24917
|
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: [AL-07, isUrbanRuralMixed, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanRuralMixed Context triple: [AL-07, isUrbanRuralMixed, true]
-
A.
hasUrbanRuralMix
chosen
Indicates that something exhibits a combination or blend of both urban and rural characteristics or components.
-
B.
isPartiallyUrbanized
Indicates that an area or region has undergone some degree of urban development but still retains significant non-urban or rural characteristics.
-
C.
urbanRuralSplit
Indicates a division or distinction between urban and rural areas, conditions, or populations.
-
D.
isRuralOrUrban
Indicates whether an entity is classified as being in a rural area or an urban 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_69e0b511ed84819099b449b4a111085c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73477957081908ab9ad11f51d15fd |
completed | April 21, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e5f60e1a888190ba75e2e900270a4e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:43 p.m.