Triple
T1510374
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tolima Department |
E31997
|
entity |
| Predicate | capital |
P234
|
FINISHED |
| Object | Ibagué |
E174123
|
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: [Tolima Department, capital, Ibagué]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ibagué Context triple: [Tolima Department, capital, Ibagué]
-
A.
Tunja
Tunja is a historic city in central Colombia known for its well-preserved colonial architecture and cultural heritage.
-
B.
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.
-
C.
Ibagué urban area
chosen
The Ibagué urban area is the principal metropolitan and economic center surrounding the city of Ibagué in central Colombia.
-
D.
Villavicencio
Villavicencio is a major Colombian city located at the foothills of the Andes, known as a gateway to the Llanos (eastern plains) region.
-
E.
Santa Marta
Santa Marta is a historic Caribbean port city in northern Colombia and one of the oldest surviving Spanish settlements 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_69a885e8caf88190a5fbb6159ce87786 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a907d4edd48190a03c85e1a0cc02b1 |
completed | March 5, 2026, 4:34 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad468cd3b88190916a6363884d664b |
completed | March 8, 2026, 9:51 a.m. |
Created at: March 4, 2026, 7:26 p.m.