Triple
T12745595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cerro Machín |
E304595
|
entity |
| Predicate | nearbyCity |
P350
|
FINISHED |
| Object | Ibagué |
E772216
|
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: Ibagué | Statement: [Cerro Machín, nearbyCity, Ibagué]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ibagué Context triple: [Cerro Machín, nearbyCity, Ibagué]
-
A.
Ibagué
chosen
Ibagué is a city in central Colombia that serves as the capital of the Tolima Department and is known for its musical heritage and cultural festivals.
-
B.
Cartagena del Chairá
Cartagena del Chairá is a rural municipality in southern Colombia’s Caquetá Department, known for its Amazonian rainforest environment and history of armed conflict presence.
-
C.
Tunja
Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
-
D.
Calarcá
Calarcá is a Colombian town and municipality in the coffee-growing Quindío Department, known for its cultural heritage and role in the Coffee Cultural Landscape.
-
E.
Suesca
Suesca is a Colombian town in the department of Cundinamarca, renowned for its dramatic rock cliffs that make it a popular destination for rock climbing and outdoor recreation.
- 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_69d7bdf1426c8190a4402e1c4cdec33a |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d96bd42fe08190a85467b1a998d2af |
completed | April 10, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e25d24e481908253e1af630835f1 |
completed | May 3, 2026, 5:51 a.m. |
Created at: April 9, 2026, 5:26 p.m.