Triple
T21468593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Rafael |
E529661
|
entity |
| Predicate | distanceToTalca_km |
P144469
|
FINISHED |
| Object | approximately 12 |
—
|
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: approximately 12 | Statement: [San Rafael, distanceToTalca_km, approximately 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToTalca_km Context triple: [San Rafael, distanceToTalca_km, approximately 12]
-
A.
distanceFromSantiago
Indicates the spatial distance between a given entity and the location of Santiago.
-
B.
distanceToIquique_km
Indicates the physical distance, measured in kilometers, between a given location and the city of Iquique.
-
C.
distanceToSantiago_km
Indicates the physical distance, measured in kilometers, between a given location and Santiago.
-
D.
distanceToTemuco
Indicates the measured spatial distance between a given place or object and the location of Temuco.
-
E.
distanceToNeuquénCity_km
Indicates the physical distance, measured in kilometers, between an entity and the city of Neuquén.
- 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_69e0c459acb481909bb6ee452a0045c7 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9e9f58f6c8190a3d2fc8f820a9925 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
| PDg | Predicate description generation | batch_69e6386c5a4481909c37f7de7e9fc025 |
completed | April 20, 2026, 2:30 p.m. |
Created at: April 16, 2026, 6:16 p.m.