This task is about classifying the similarity of two sentences. The sentences can be classified as (a) SIMILAR - similar to each other, and (b) DISSIMILAR - not similar to each other. Sentences that have the same RDF relationship in terms of [subject, predicate, object] are similar to each other. The input is a list of two sentences and the output is either SIMILAR or DISSIMILAR.

Example Input: ['United States national Elliot See was born in Dallas. He graduated from the University of Texas at Austin, an affiliation of the university of Texas system, and later served as a test pilot. He passed away in St. Louis.', 'Elliot See has died in St Louis. Born in Dallas he was a US national and attended the University of Texas at Austin which is affiliated the the University of Texas system. He then became a test pilot,.']
Example Output: SIMILAR

Example Input: ['Cocum is a Japanese coffee shop which is good for families.', 'The score when they had 62 points was 2–1 (so.']
Example Output: DISSIMILAR

Example Input: ["The Waterman is in the city centre with an average rating, serving French food for less than £20. They aren't family-friendly.", "The Waterman is a place to get French food for less than £20 in the city centre. They have an average customer rating and aren't family-friendly."]
Example Output:
SIMILAR