Triple
T14794835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caldas |
E347746
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Chinchiná |
E195922
|
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: Chinchiná | Statement: [Caldas, hasMunicipality, Chinchiná]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chinchiná Context triple: [Caldas, hasMunicipality, Chinchiná]
-
A.
Chinchiná
chosen
Chinchiná is a Colombian town and municipality known for its coffee production and location in the central Andean region.
-
B.
Veragua
Veragua was a historical territory in Central America associated with the hereditary dukedom granted to the descendants of Christopher Columbus under the title Duke of Veragua.
-
C.
Colombia
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.
-
D.
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.
-
E.
Tocaima
Tocaima is a historic Colombian town in the Cundinamarca Department, known for its warm climate and thermal springs.
- 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.