Triple
T6672841
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Curacaví |
E151772
|
entity |
| Predicate | ruralUrbanCharacter |
P60791
|
FINISHED |
| Object | predominantly rural |
—
|
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: predominantly rural | Statement: [Curacaví, ruralUrbanCharacter, predominantly rural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ruralUrbanCharacter Context triple: [Curacaví, ruralUrbanCharacter, predominantly rural]
-
A.
hasSuburbanCharacter
Indicates that something possesses qualities or features typically associated with suburban areas, such as lower density, residential focus, and car-oriented development.
-
B.
isRuralOrUrban
chosen
Indicates whether an entity is classified as being in a rural area or an urban area.
-
C.
isRural
Indicates that something is located in, characteristic of, or associated with a countryside or non-urban area.
-
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.
urbanRuralSplit
Indicates a division or distinction between urban and rural areas, conditions, or populations.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6ce738fe88190a5557900efeec7ec |
completed | March 27, 2026, 6:37 p.m. |
| PD | Predicate disambiguation | batch_69c6ad09974c81908784300ae218961f |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:03 p.m.