Module tf.about.manual

Search manual


1. patterns

You can search the corpus by means of patterns. Several patterns work together at different levels of the corpus. When all patterns match, we have a result. All results will be listed in the table on the right.

A pattern can be as simple as a word, and then it will find all occurrences of that word. But they can be way more sophisticated than that. See Search patterns below for a crash course.

See Meaning below for what the meaning is of multiple patterns working together.

2. show text of a layer
You can click on the name of each layer to show and hide the full text of that layer. So that you know the material in which you are searching.
3. focus

The level in the corpus that corresponds with a single row in the results table. For example, if you put focus on sentence, the results will be organized by sentence.

More or less context

By changing focus, you will see more or less context around the results.

4. execute
Whenever you change a pattern, the search results will be updated. But you can also press this button to run the search again.
5. stats
How many results there are at each level, compared to the total size of the corpus.
6. export
Export the search results as a tab-separated file (.tsv). This file can be opened in Excel. All results are exported, not only the ones that show on the current page. The level of detail depends on the currently selected focus level.
7. options
Switch between the simple interface and the full interface. There is a separate manual for the full interface: tf.about.clientmanual.
8. help
Help and info.
9. navigate

Walk through the results in various ways:

  • manual entry of the position number,
  • small jumps back and forth,
  • big strides with the slider.

If you do this often: there are handy keyboard shortcuts. See below.

10. position
The current position in the results table is marked.
11. previous position
The previous position in the results table is also marked, in a slightly less conspicuous way.
12. highlighting

The portions in the layer that match the corresponding pattern are highlighted.


When you export results, the highlight information is lost.


There is an option to retain highlight information in exports. For that you have to use the full interface.

13. links to online
The top level layers are linked to an online representation of the corpus. For example, for NENA it is the GitHub repository where the source texts are stored. For the BHSA it is SHEBANQ.

Search patterns

Here is a crash course in increasingly complex search patterns. We only give examples and a bit of explanation.

Simple words

mute is a pattern that matches all occurrences of the string mute. Case is not important, and it does not have to be a whole word.

hint !!! "Case sensitive search" If the case of letters is important, use the full interface, where you can switch it on and off.

Word boundaries

We can reckon with word boundaries:

  • \bmute\b matches mute but only if it is a separate word.
  • \bmute matches words that start with mute
  • mute\b matches words that end in mute
Line boundaries

We can reckon with line boundaries:

  • ^mute$ matches mute but only if it occupies a complete line;
  • ^mute matches occurrences of mute at the start of a line;
  • mute$ matches occurrences of mute at the end of a line.

match literally

You can take these special characters literally by using \$ and \^.


m.te matches mate, mbte, mcte, m,te, m te, etc.

The . matches any character, except a newline.


To match a newline, use \n

Small variations

m[aeiou]te matches mate, mete, mite, mote, mute.

With [ ] you can define a character class. Everything in the class is matched.

There are more possibilities:

  • [0-9] matches all single digits
  • [a-z] matches all single letters
  • [p-w] matches all single letters between p and w (including)
  • [a-ep-w:;!?] matches the letters a to e, p to w, :, ;, !, and ?.
  • [a-e-] matches the letters a to e and -. (The - should be right before the ]).
  • [^aeiou] matches every character other than a vowel
  • [(){}\[\]] matches the letters (, ), {, }, [, and ]. Note that you have to use \ in front of the [ and ] to undo their special meaning.
Smaller variations
mute|nase matches either mute or nase.

We can group patterns

  • mu(t|r)e matches mu followed by either t or r, followed by e
  • (^|a)mute matches mute at the start of a line, or amute

We can specify that a pattern should match a number of times:

? means 0 or 1 times:
p[aeiou]?r matches a p followed by an optional vowel, followed by an r.
+ means 1 or more times:
p[aeiou]+r matches a p followed by at least one vowel, possibly more vowels, followed by an r.
* means arbitrary many times:
p[aeiou]*r matches a p followed by any number of vowels, possibly none at all, followed by an r.
{3,7} means at least 3 and at most 7 times
ma{3,7}t matches an m, then 3-7 a, and then a t.
{3,} means at least 3 times
ma{3,}t matches an m, then at least 3 a, and then a t.
{,7} means at most 7 times
ma{,7}t matches an m, then at most 7 a, and then a t.

The quantifiers ?, +, * try to make as many repetitions as the text admits. But you can reign them in so that they make as few repetitions as possible, by putting a ? behind them: ??, +?, *?.

Suppose we search the string

mute aaaa nase bbbb nase cccc
  • mute .* nase matches mute aaaa nase bbbb nase
  • mute .*? nase matches mute aaaa nase


  • mute .* nase bbbb matches mute aaaa nase bbbb

Initially, the .* takes us to the second nase, but the pattern wants a bbbb at the end, so it has gone to far and it will, reluctantly, backtrack, until the match is found.

  • mute .*? nase cccc matches mute aaaa nase bbbb nase cccc

Initially, the .*? takes us to the first nase, but the pattern wants a cccc at the end, so it has gone not far enough and it will, reluctantly, go further, until the match is found.


By using the constructions we have so far, we can specify ever more complex patterns.

  • \b[^aeiou]{2}[aeiou][^aeiou]+\b matches a word consisting of exactly 2 consonants, one vowel, and then one or more consonants.
  • \b([^aeiou][aeiou][^aeiou]|[^aeiou]{2}[aeiou][^aeiou]{2})\b matches a word of shape CVC or CCVCC.

If there is more than one group, you can refer to them by \1, \2, etc.

More power

Groups between ( ) have memory. If something is matched by it, you can reuse is later in the pattern. If we have one pair of ( ), then \1 refers to whatever that group matched.

  • ([^aeiou])\1 matches twice the same consonant, no matter which one
  • ([^aeiou])\1{3} matches 4 times the same consonant. This will find words such as xirrrr.
  • (\b([a-z]+)\b).*?\b\1\b finds twice the same word in a sentence

Note that [^aeiou]{4} will find 4 consonants, but they do not have to be the same.

Ultimate power

This is not all. Much more can be done with patterns. The full story is here:



Your corpus is divided into levels, e.g. text/line/sentence/word/.

At each level there are objects in the corpus and they can be represented in certain ways:

  • text are represented by their titles;
  • lines are represented by their numbers;
  • words are represented by the strings of which they are composed.

In order to search, you specify search patterns for as many of the available layers as you want.

When the search is performed, all these layers will produce results, and the results in one layer will be "intersected" with the results in all other layers.

Beware of complicated criteria

Before you devise sophisticated criteria, note that this search engine is not very refined in taking intersections. It takes the intersections of the joint results of the matches in the layers. It will not take the intersections of the individual matches.

The bottom-line is: use the search tool to grab the things that are potentially of interest. If you need to pinpoint further, export the results to Excel and use other tools/methods to achieve that.

If you need more information in this, consult the manual for the full interface: tf.about.clientmanual.


You can export the search results to Excel (or rather, a tab-separated file, .tsv). When you do that, all results will get exported, not only the ones that show on the interface.

The organization of the exported results reflects the interface. Here are screenshots of an export where the focus is on sentences, and one with the focus on words. Observe the different amount of context in the export.


Keyboard shortcuts

Keyboard shortcuts need to be pressed with modifier keys. It depends on your browser which ones. Here is the list, by browser and platform:

browser Windows - Linux - Mac
Firefox Alt + Shift Alt + Shift Ctrl + Option
Chrome Alt + Shift Alt Ctrl + Option
Edge Alt + Shift Ctrl + Option
Safari Ctrl + Option

Having figured that out, you can use those modifier keys together with a letter to perform the following actions:

shortcut action
n next position
p previous position
b back a batch
f forward a batch
s start
e end
m manually type the position in the box
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.. include:: ../docs/about/