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: The club Citizen achieved its last top division title in n / a.
Example Output: [['citizen', 'LAST_TOP_DIVISION_TITLE', 'n/a']]

Example Input: Near Café Sicilia is the children friendly, fast food coffee shop The Punter, which has a 1 out of 5 customer rating and a high price range.
Example Output: [['The Punter', 'eatType', 'coffee shop'], ['The Punter', 'food', 'Fast food'], ['The Punter', 'priceRange', 'high'], ['The Punter', 'customer rating', '5 out of 5'], ['The Punter', 'familyFriendly', 'yes'], ['The Punter', 'near', 'Café Sicilia']]

Example Input: In the city centre, Fitzbillies is a adult fast food coffee shop with high price range and a customer rating of 1 out of 5.
Example Output:
[['Fitzbillies', 'eatType', 'coffee shop'], ['Fitzbillies', 'food', 'Fast food'], ['Fitzbillies', 'priceRange', 'high'], ['Fitzbillies', 'customer rating', '1 out of 5'], ['Fitzbillies', 'area', 'city centre']]