Sentence examples for input sentences from inspiring English sources

Tokenization: input sentences are broken up into tokens (words).

The system selects only 131 candidate sentences out of 2275 input sentences for OCQs formation.

To identify the simple sentences we have analyzed the dependency structures of the input sentences.

For this reason, we used Stanford Parser to analyze grammatical structure of input sentences.

We present different constructions for nonprioritized belief revision, that is, belief changes in which the input sentences are not always accepted.

Disjunction is a binary truth-function, the output of which is a sentence true if at least one of the input sentences (disjuncts) is true, and false otherwise.

Each element value is the frequency of the word or POS in the input sentence.

Parsing is the task of analyzing grammatical structures of an input sentence and deriving its parse tree.

The latter permits analyses to start from any dynamically chosen positions within the input sentence, combining bottom-up and top-down processing without redundancy.

Sumita et al. (2005) developed fill-in-the-blank questions by replacing verbs with gaps in an input sentence.

From the next test follows that the input sentence length plays a great role in recognition stability (see Figure13).