Triple
T516805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ngäbere |
E10726
|
entity |
| Predicate | spokenIn |
P2266
|
FINISHED |
| Object | Panama |
E1142
|
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: Panama | Statement: [Ngäbere, spokenIn, Panama]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Panama Context triple: [Ngäbere, spokenIn, Panama]
-
A.
Panama
chosen
Panama is a Central American country known for the Panama Canal, a major international shipping route connecting the Atlantic and Pacific Oceans.
-
B.
Costa Rica
Costa Rica is a Central American country renowned for its political stability, rich biodiversity, and strong environmental conservation efforts.
-
C.
Nicaragua
Nicaragua is a Central American country known for its volcanic landscapes, large lakes, and colonial-era architecture.
-
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.
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.
- 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_69a2e84a0d08819087e01863fcd9abf1 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f184c3a481909bf60bb627b0ea88 |
completed | Feb. 28, 2026, 1:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac1185da8c8190a70f4fd885bbe209 |
completed | March 7, 2026, 11:52 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.