Triple
T4582487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Copenhagen Accord |
E101885
|
entity |
| Predicate | draftedBy |
P2210
|
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: [Copenhagen Accord, draftedBy, Brazil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brazil Context triple: [Copenhagen Accord, draftedBy, 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.
Brazil
Brazil is a 1985 dystopian science fiction film known for its darkly satirical portrayal of a bureaucratic, totalitarian society and its distinctive, surreal visual style.
-
C.
Brasyl
Brasyl is a science fiction novel by Ian McDonald that intertwines multiple timelines in Brazil to explore themes of quantum reality, culture, and globalization.
-
D.
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.
-
E.
Portuguesa State
Portuguesa State is a landlocked agricultural region in western Venezuela known for its extensive plains and significant crop production, particularly of rice and corn.
- 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_69bd43d4ce208190b53158c882b222e3 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd59029568819091db1e77a9a2ec41 |
completed | March 20, 2026, 2:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bde09015c48190b4f992f3f95023cf |
completed | March 21, 2026, 12:04 a.m. |
Created at: March 20, 2026, 1:10 p.m.