We describe a system proposed for measuring the degree of relational similarity beetwen a pair of words at the Task #2 of Semeval 2012. The approach presented is based on a vectorial representation using the following features: i) the context surrounding the words with a windows size = 3, ii) knowledge extracted from WordNet to discover several semantic relationships, such as meronymy, hyponymy, hypernymy, and part-whole between pair of words, iii) the description of the pairs with their POS tag, morphological information (gender, person), and iv) the average number of words separating the two words in text.
The BUAP system REF represented each word pair as a whole by a vector of 4 different types of features: context, WordNet, POS tags and the average number of words separating the two words in text.
BUAP: A First Approximation to Relational Similarity Measuring
SemEval
Computer Science