For the following exercises, use functions beyond querying in CQP, such as sorting, sampling, randomizing and reducing. In addition, some of these exercises with require the use of positional attributes, like class or pos, and structural attributes. Like before, you will also have to be familiar with generating frequencies lists, exporting concordances into a specific file formats.

If you need help on how to work with concordances, have a look at this Wiki-page.

Query the BNC-BABY for the lemma furthermore.

1. Group the matches in the concordance by the structural attribute text_domain. What is the most frequent text domain?
2. Group the matches in the concordance by the structural attribute text_publication_date. What is the most frequent time period?

Investigate the verbs gather and collect in the BNC. Explore the occurrence of the verbs in terms of their complementation patterns.

1. Set the context to 1 sentence.
2. Display the structural attribute text_id in your concordance.
3. Search for one verb (case-insensitive) at a time using a complex query, where you search for the lemma, and specifying the word form with either a pos- or class-tag.
4. Randomize the data, then reduce it to 50 concordance lines.
5. Export your concordance as txt-file, using the tidycwb.pl.
6. Repeat these steps for the other verb.

1. Set the context to 60 characters.
2. Display the structural attributes text_id and text_n_s in your concordance.
3. Search for the lemma love as a verb in the BNC-BABY.
4. Save the concordance in a variable, randomize it (with the variable) and extract a sample of 50 concordances.
5. Generate a frequency list of all words directly following your match in the concordance (case-insensitive) and export that frequency list into a CSV-file, using the tidycwb.pl.

Find the solutions for the exercises here: Working with Concordances – Solutions