Triple
T16564124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mauro Castillo |
E402412
|
entity |
| Predicate | workLocation |
P7
|
FINISHED |
| Object | Colombia |
E12035
|
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: Colombia | Statement: [Mauro Castillo, workLocation, Colombia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Colombia Context triple: [Mauro Castillo, workLocation, Colombia]
-
A.
Colombia
chosen
Colombia is a transcontinental country in northern South America, known for its diverse landscapes from Andes mountains to Amazon rainforest, rich cultural heritage, and major cities like Bogotá and Medellín.
-
B.
Colombia
Colombia is a station on Madrid's Metro network, serving Line 8 and acting as an important interchange point in the city's public transportation system.
-
C.
Chinchiná
Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
-
D.
Ecuador
Ecuador is a South American country on the Pacific coast, known for its diverse geography that includes part of the Amazon rainforest, the Andean highlands, and the Galápagos Islands.
-
E.
Venezuela
Venezuela is a South American country known for its vast oil reserves, diverse landscapes ranging from Caribbean coastlines to Andean mountains and Amazon rainforest, and its Spanish-speaking population.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3577043048190bc9bcf55069b769f |
completed | April 18, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a006edfe7f08190857fc6f66f3be9a0 |
completed | May 10, 2026, 11:41 a.m. |
Created at: April 10, 2026, 5:15 a.m.