Sentence examples for corpus input from inspiring English sources

In the second evaluation round, using the Wiki corpus input, the judges reached an agreement in 68% of the triples.

This tool takes a large-scale text corpus as input and produces the word vectors as output.

Word2vec uses a large-scale text corpus as input and produces vector representations of words by constructing a vocabulary and learning how to describe words outside the vocabulary from those inside it [8].

The general focus is to apply Deep Learning algorithms to train the high-level data representation patterns based on a portion of the available input corpus, and then utilize the remaining input corpus with the learnt patterns for extracting the data abstractions and representations.

The first part identifies simple sentences from the input corpus.

We have performed two evaluation rounds, each one using a different input corpus.

Hence, to generate sufficient number of OCQs by our proposed system, a huge size of input corpus is a prerequisite.

To identify the informative sentences, first we have collected the simple sentences from the dependency parsing of the input corpus.

In order to generate the questions, the system first extracts a set of informative sentences from the given input corpus.

An important problem is whether to utilize the entire Big Data input corpus available when analyzing data with Deep Learning algorithms.

Capturing these complex representations requires massive amounts of data for the input corpus, and producing labeled data from this massive input is a difficult task.