1. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors using features learned during training; integrating verb of interest and word of interest position relative to the word to be labeled by employing a linear layer that is adapted to the input sentence; and applying linear transformations and squashing functions to the vectors to predict semantic role labels.
1. A method for semantic extraction using neural network architecture, comprising: indexing an input sentence and providing position information for a word of interest and a verb of interest; converting words into vectors using features learned during training; integrating verb of interest and word of interest position relative to the word to be labeled by employing a linear layer that is adapted to the input sentence; and applying linear transformations and squashing functions to the vectors to predict semantic role labels. 8. The method as recited in claim 1 , wherein converting words into vectors includes outputting vectors of different dimensions for each word, each word of interest position and each verb position.