This task is about using the specified sentence and converting the sentence to Resource Description Framework (RDF) triplets of the form (subject, predicate object). The RDF triplets generated must be such that the triplets accurately capture the structure and semantics of the input sentence. The input is a sentence and the output is a list of triplets of the form [subject, predicate, object] that capture the relationships present in the sentence. When a sentence has more than 1 RDF triplet possible, the output must contain all of them.

Example Input: Rosberg continued to drive for Mercedes in the 2013 season, winning 2 out of 19 races and scoring 171 points.
Example Output: [['Formula One', 'POINTS', '171'], ['2013', 'TEAM', 'Mercedes AMG Petronas F1 Team'], ['19', 'WINS', '2'], ['Formula One', 'RACES', '19'], ['2013', 'SERIES', 'Formula One'], ['[TABLECONTEXT]', '[TITLE]', 'Nico Rosberg'], ['[TABLECONTEXT]', 'SEASON', '2013']]

Example Input: For an average cost and dining experience, The Wrestlers is an average rated Japanese dining experience.
Example Output: [['The Wrestlers', 'food', 'Japanese'], ['The Wrestlers', 'customer rating', '3 out of 5']]

Example Input: The 2006 population count of the local government area Coober Pedy was 1996.0.
Example Output:
[['Coober Pedy', 'LAND_AREA_(KM²)', '77,8'], ['Coober Pedy', 'POP._2006', '1996'], ['Coober Pedy', 'EST.', '1987'], ['Coober Pedy', 'MAJOR_TOWN', 'Coober Pedy'], ['Coober Pedy', 'TOWNS', '1'], ['Coober Pedy', 'TYPE', 'District Council'], ['Coober Pedy', 'DENSITY_KM_−2', '25656']]