Sentence examples for predicted sentence from inspiring English sources

The output of our classifiers is judged to be correct if the predicted sentence corresponds to the labelled one.

More subtly, if none of the predicted sentences is entirely correct, yet collectively they contain the words that were spoken, the user can simply slide his finger across the appropriate words to link them up.In a sense, all Parakeet is doing is allowing the user to see which alternative words or sentences the program would have predicted.

To see if this was so, they trained models to predict sentence importance on redacted datasets, where either nouns, verbs, adjectives, adverbs, or function words were removed and compared them to models trained on the original data.

The analysis yielded a) a second model for predicting the verdict (see Table 4), and b) a second model for predicting sentence length (see Table 5).

This was done using a second logistic regression analysis for predicting the verdict and a second multiple linear regression to predict sentence length.

Their results show that degree centrality explains the likelihood of a guilty or innocent verdict but is less successful in predicting sentence length [1].

Due to the contamination of our text sample by new line characters, this feature does no longer reliably predict sentence boundaries.

The only statistically significant cross loading here is that between language at Time 2 and sentence repetition at Time 3, indicating that variation in language ability at Time 2 predicts additional variability in sentence repetition at Time 3, over and above the autoregressive effect (i.e. what is already predicted by sentence repetition at the previous time point).

The approach includes four steps: Direct dictionary lookup is done for each predicted positive sentence to detect whether there are relevant genes appearing in the sentence.

After cerebellar rTMS, listeners showed delayed eye fixations to target objects predicted by sentence content, while there was no effect on eye fixations in sentences without predictable content.

For the remaining predicted positive sentences with no relevant gene mentioned, we assume that prior sentences would contain the gene information.