Triple
T7381862
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Magdalena River |
E170274
|
entity |
| Predicate | passesNear |
P416
|
FINISHED |
| Object | Magangué |
E481842
|
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: Magangué | Statement: [Magdalena River, passesNear, Magangué]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Magangué Context triple: [Magdalena River, passesNear, Magangué]
-
A.
Magangué
chosen
Magangué is a Colombian city located in the department of Bolívar, known as an important commercial and river port along the Magdalena River.
-
B.
Tucupita
Tucupita is a small Venezuelan city that serves as the capital of Delta Amacuro state and the main urban center near the Orinoco Delta.
-
C.
Rurrenabaque
Rurrenabaque is a small Bolivian town known as a popular gateway to the Amazon rainforest and nearby Madidi National Park.
-
D.
Nova Mamoré
Nova Mamoré is a municipality in the Brazilian state of Rondônia, located in the western Amazon region near the border with Bolivia.
-
E.
Sibaté
Sibaté is a municipality in central Colombia known for its agricultural production and proximity to Bogotá within the Cundinamarca Department.
- 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_69c68a5d0ed08190b6d361e68f813330 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1c9a3c48190972126c19aa31dca |
completed | March 27, 2026, 9:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c810e879e88190a421409194868587 |
completed | March 28, 2026, 5:33 p.m. |
Created at: March 27, 2026, 3:08 p.m.