Triple
T834340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aracataca, Magdalena, Colombia |
E18036
|
entity |
| Predicate | distanceToSantaMarta |
P20924
|
FINISHED |
| Object | about 80 km |
—
|
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: about 80 km | Statement: [Aracataca, Magdalena, Colombia, distanceToSantaMarta, about 80 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToSantaMarta Context triple: [Aracataca, Magdalena, Colombia, distanceToSantaMarta, about 80 km]
-
A.
distanceFromCusco
Indicates the measured spatial distance between a given location or entity and the city of Cusco.
-
B.
distanceToSantiago_km
Indicates the physical distance, measured in kilometers, between a given location and Santiago.
-
C.
distanceFromSantiago
Indicates the spatial distance between a given entity and the location of Santiago.
-
D.
distanceToSouthAmerica
Indicates the spatial distance between a given entity’s location and the continent of South America.
-
E.
distanceToSanDiego
Indicates the measured or estimated distance between a given entity’s location and the city of San Diego.
- 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_69a49389f44881909a608fb27d89f247 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4abccb94881909cd49aa3fd986b4a |
completed | March 1, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7c7df881909c539c3ab8ff0367 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab9634948190b25ea1b2e34df87d |
completed | March 1, 2026, 9:11 p.m. |
Created at: March 1, 2026, 7:38 p.m.