Sentence examples for word extract from inspiring English sources

Exact(1)

On Friday 13 September, a 5,600 word extract, welded together for the Guardian, landed on the internet with the force of a small bomb.

Similar(59)

Mr. Mehlman, who had not yet uttered a word, extracted himself from the discussion, saying the connection was bad and that he had to catch a plane from Washington to join the party meeting in Austin.

The 26,000-word extract in the Observer of 11 June 1956 not only caused a newspaper sensation, it also consolidated Crankshaw's reputation as the pre-eminent British press authority on Soviet affairs.

The work in this paper modifies the original Khoja stemmer to generate 3 parts [the words prefix, suffix (if any), and the word stem] by keeping any removed characters from the word if the word roots extracted word is divided into the prefix, stem and suffix.

On this podcast, he also talks about his most recent magazine article (on Hillary Clinton's fraught relationship with the press), his winding path to The New Yorker (which included stints in Bobby Kennedy's campaign and in the off-track betting industry), and how he goes about, in Thompson's words, extracting "information from places you should not be able to extract information".

Terms are words extracted from a text describing the subjects covered in it [20].

The sentiment words extracted through topic models as candidate aspects are pruned by considering them as non-aspect adjectives.

The classifier builds a dictionary using histograms from a series of "visual words" extracted from the training image dataset.

A complete filled form, sample lines of text and some words extracted from a sample form in the database are illustrated in Fig. 1.

We have extended the text analysis of TMM13 [12], and we have included affective modeling of single words extracted from the subtitles and transcripts included in the database.

Rapid abundance estimation and sequence classification tools [16, 17] use longer words and derive a large speed advantage by utilizing, instead of word counts, a simple match between the words extracted from sequence data to identify the similarity between two sequences.

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