Triple
T15458092
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eje Cafetero |
E371825
|
entity |
| Predicate | hasProvince |
P285
|
FINISHED |
| Object | Caldas |
E347746
|
NE 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: Caldas | Statement: [Eje Cafetero, hasProvince, Caldas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Caldas Context triple: [Eje Cafetero, hasProvince, Caldas]
-
A.
Caldas
chosen
Caldas is a department in west-central Colombia known for its coffee-growing region, mountainous landscapes, and part of the Paisa cultural area.
-
B.
Caldas
Caldas is a municipality in the Antioquia Department of Colombia, located in the southern part of the Aburrá Valley metropolitan area near Medellín.
-
C.
Sogamoso
Sogamoso is a Colombian city in the Andean region known historically as a major religious and cultural center of the Muisca civilization and today for its industry and mining.
-
D.
Calarcá
Calarcá is a Colombian town and municipality in the coffee-growing Quindío Department, known for its cultural heritage and role in the Coffee Cultural Landscape.
-
E.
Cajicá
Cajicá is a Colombian town and municipality in the department of Cundinamarca, known for its colonial heritage and proximity to Bogotá.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d85cc8bd308190886949510b42e764 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f1623f0819086f6fc2bfd536609 |
completed | April 16, 2026, 1:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff21b7b600819081a6087bd6309237 |
completed | May 9, 2026, 11:59 a.m. |
Created at: April 10, 2026, 3:32 a.m.