Triple
T201457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza de Armas de La Serena |
E4513
|
entity |
| Predicate | hasNearbyStreet |
P8235
|
FINISHED |
| Object | main streets of downtown La Serena |
—
|
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: main streets of downtown La Serena | Statement: [Plaza de Armas de La Serena, hasNearbyStreet, main streets of downtown La Serena]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyStreet Context triple: [Plaza de Armas de La Serena, hasNearbyStreet, main streets of downtown La Serena]
-
A.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
B.
hasNearbySquare
Indicates that one entity has at least one square-shaped entity located close to it in space.
-
C.
isDowntownEndpointOf
Indicates that a location serves as the downtown terminus or endpoint of a route, line, or path.
-
D.
nearbyCurrent
Indicates that one entity is located close to another entity at the present moment or in the current context.
-
E.
hasNeighbourhood
Indicates that one entity is located within, or is associated with, a particular neighborhood area of another entity.
- F. None of above. chosen
Provenance (4 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_69a25737567c81908f9c505300239181 |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c2ead8481909996042efcae5e9d |
completed | Feb. 28, 2026, 3:08 a.m. |
| PD | Predicate disambiguation | batch_69a25b4a0d448190a6fa6aeb30dc7e13 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25c2bda788190bcfc0bc94686f9e0 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:51 a.m.