Then W 1 is applied to each possible window in the shortest dependency path to produce a feature map: Next, we adopt the widely-used max-over-time pooling operation (Collobert et al., 2011), which can retain the most important features, to obtain the final representation L from the feature map.
like other relation classification systems, we also incorporate some lexical level features such as named entity tags and WordNet hypernyms, which prove useful to this task.