Triple
T14794772
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paisa region |
E347745
|
entity |
| Predicate | hasMajorCity |
P316
|
FINISHED |
| Object | Medellín |
E73076
|
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: Medellín | Statement: [Paisa region, hasMajorCity, Medellín]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Medellín Context triple: [Paisa region, hasMajorCity, Medellín]
-
A.
Medellín
chosen
Medellín is Colombia’s second-largest city, known for its mountainous setting, innovative urban development, and vibrant cultural life.
-
B.
Bogotá and Medellín
Bogotá and Medellín are Colombia’s two largest and most important cities, serving as major centers of politics, culture, and commerce in the country.
-
C.
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.
-
D.
Manizales
Manizales is a mountainous Colombian city known for its coffee production, cool climate, and location in the central Andes.
-
E.
Bogotá
Bogotá is the high-altitude capital and largest city of Colombia, known as a major political, economic, and cultural center in South America.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5fdd548190a2ee5e668c2b20b4 |
completed | April 14, 2026, 11:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe24bea4408190975f4856cc02580e |
completed | May 8, 2026, 6 p.m. |
Created at: April 10, 2026, 1:31 a.m.