Triple
T5538494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peñaflor |
E145227
|
entity |
| Predicate | suburbanRelation |
P5065
|
FINISHED |
| Object | Santiago metropolitan suburbs |
—
|
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: Santiago metropolitan suburbs | Statement: [Peñaflor, suburbanRelation, Santiago metropolitan suburbs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: suburbanRelation Context triple: [Peñaflor, suburbanRelation, Santiago metropolitan suburbs]
-
A.
suburbanBelt
Indicates that one area forms a suburban belt or ring surrounding another, typically as a zone of residential or peripheral development around a core urban center.
-
B.
isResidentialSuburbOf
chosen
Indicates that one area is a residential suburb that is part of or lies within the urban region of another area.
-
C.
hasNearbySuburb
Indicates that one location has another location as a suburb situated in close geographic proximity.
-
D.
landRelation
Indicates a spatial or ownership-based relationship between entities and a specific piece or area of land.
-
E.
isSuburbanStationOf
Indicates that a station is located in a suburban area and functionally serves as a subsidiary or outlying station of a main or central station.
- 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_69c008fa64888190adae56c8f9ea4031 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01fb2fe488190808e02ce5aabb2ad |
completed | March 22, 2026, 4:58 p.m. |
| PD | Predicate disambiguation | batch_69c01b0c50e48190a1b03ecd20ca440b |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:35 p.m.