Triple
T7519140
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aburrá Valley |
E177722
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Bello |
E179159
|
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: Bello | Statement: [Aburrá Valley, contains, Bello]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bello Context triple: [Aburrá Valley, contains, Bello]
-
A.
Bello
chosen
Bello is a Colombian city in the Aburrá Valley metropolitan area, just north of Medellín, known for its industrial activity and dense urban development.
-
B.
Bonomi
Bonomi is an Italian surname most notably associated with Ivanoe Bonomi, a prominent early 20th-century Italian politician and statesman.
-
C.
Belli
The Belli were a prominent ancient Celtiberian tribe inhabiting the central-eastern Iberian Peninsula, known for their role in conflicts with Rome during the 2nd century BCE.
-
D.
Tota
Tota is a town in the Boyacá Department of Colombia, known for its proximity to Lake Tota, one of the country’s largest and highest lakes.
-
E.
Bracciolini
Bracciolini is an Italian surname most famously associated with Poggio Bracciolini, a Renaissance humanist and manuscript hunter who helped rediscover many classical Latin texts.
- 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_69c69f2891148190a484f3b8222c6f1b |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f5f850c081909e697219071293fc |
completed | March 27, 2026, 9:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8462610b481909fa74023852b0154 |
completed | March 28, 2026, 9:20 p.m. |
Created at: March 27, 2026, 3:46 p.m.