Triple
T4637047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Marta |
E101556
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Barranquilla |
E73884
|
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: Barranquilla | Statement: [Santa Marta, nearbyCity, Barranquilla]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barranquilla Context triple: [Santa Marta, nearbyCity, Barranquilla]
-
A.
Barranquilla
chosen
Barranquilla is a major port city on Colombia’s Caribbean coast, known for its vibrant culture and famous Carnival festival.
-
B.
Bucaramanga
Bucaramanga is a major city in northeastern Colombia known for its mountainous setting, pleasant climate, and role as an important commercial and industrial center.
-
C.
Santa Marta
Santa Marta is a historic Caribbean port city in northern Colombia and one of the oldest surviving Spanish settlements in South America.
-
D.
Medellín
Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
-
E.
Pereira
Pereira is a major Colombian city known as the capital of the Risaralda department and an important economic and cultural center in the country's coffee-growing region.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a62a9e48190b0cf1cbcc51f00c0 |
completed | March 20, 2026, 2:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bdfacba5fc8190bc86157ee5719ced |
completed | March 21, 2026, 1:56 a.m. |
Created at: March 20, 2026, 1:13 p.m.