Sentence examples for most frequent verbs from inspiring English sources

From each of the compiled lists of frequently occurring verbs, around 20 most frequent verbs are selected and inserted to the semantic vocabulary.

Then we analyze the ten most frequent verbs of our corpora and their projecting characteristics.

Our next step was to explore the ten most frequent verbs in both corpora.

Besides, we are going to explore projecting characteristics of our corpus in general, and of the ten most frequent verbs in this corpus, in particular.

Having determined the ten most frequent verbs, we then retrieved all sentences containing any form of these verbs from the CYP450 portion of the PennBioIE corpus.

We approached the problem by determining what the most frequent verbs are in biomedical text, then analyzing those verbs and their nominalizations in terms of the alternations that they participate in.

The list may assist in the development of predicate sets resembling a certain relation type that covers the most frequent verb forms used in the biomedical literature.

For example, the most frequent verb of the event Localization is 'localize', which only takes a subject; therefore, the Theme argument is mapped to the subject, and atLoc and toLoc, specific to this reaction type, are added as keywords.

SVO queries are generated from the mapping shown in Table 1 as follows: the Cause argument in the event representation, when present, is used as the subject, the most frequent verb for each reaction type as annotated in the GENIA corpus (Kim et al., 2008) is used as the verb and the Theme argument is used as the object.

Figure 3 illustrates the most frequent 450 verb-candidates being all correctly labeled as verb.

The task is interesting because although most of the verbs in English (the regular verbs) form the past tense by adding the suffix '-ed', many of the most frequently verbs are irregular ('is' / 'was', 'come' / 'came'go'go' / 'went'went