Triple
T608023
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Colombia |
E12035
|
entity |
| Predicate | borderCountry |
P224
|
FINISHED |
| Object | Brazil |
E19289
|
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: Brazil | Statement: [Colombia, borderCountry, Brazil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brazil Context triple: [Colombia, borderCountry, Brazil]
-
A.
Brazil
chosen
Brazil is the largest country in South America, known for its vast Amazon rainforest, diverse culture, and major cities like São Paulo and Rio de Janeiro.
-
B.
Paraguay
Paraguay is a landlocked country in central South America known for its bilingual Spanish and Guaraní culture and its location along the Paraguay and Paraná rivers.
-
C.
Argentina
Argentina is a large South American nation known for its diverse landscapes from the Andes to the Pampas, its vibrant culture including tango and football, and its capital city Buenos Aires.
-
D.
Uruguay
Uruguay is a small South American country known for its stable democracy, high standard of living, and Atlantic coastline between Brazil and Argentina.
-
E.
Peru
Peru is a South American country known for its rich Inca heritage, diverse landscapes from Andes mountains to Amazon rainforest, and the iconic archaeological site of Machu Picchu.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49df34abc8190a578c8c2ab3d28e4 |
completed | March 1, 2026, 8:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d69ade481909322f5f28f0050e4 |
completed | March 3, 2026, 11:23 p.m. |
Created at: March 1, 2026, 7:35 p.m.