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MARC-XML is an extension to the MARC-Record distribution for working with XML data encoded using the MARC21slim XML schema from the Library of Congress. For more details see: http://www.loc.gov/standards/marcxml/

The HTML::Fraction encodes fractions as HTML entities. Some very common fractions have HTML entities (eg 1/2 is ½). Additionally, common vulgar fractions have Unicode characters (eg 1/5 is ⅕). This module takes a string and encodes fractions as entities: this means that it will look pretty in the browser.

Par is similar but superiour to the fmt(1) command included in the base system. Par is a filter that copies its input to its output, changing all white characters (except newlines) to spaces, and reformatting each paragraph. Paragraphs are separated by protected, blank, and bodiless lines (see the Terminology section for definitions), and optionally delimited by indentation (see the d option in the Options section). Each output paragraph is generated from the corresponding input paragraph as follows: 1) An optional prefix and/or suffix is removed from each input line. 2) The remainder is divided into words (separated by spaces). 3) The words are joined into lines to make an eye-pleasing paragraph. 4) The prefixes and suffixes are reattached. If there are suffixes, spaces are inserted before them so that they all end in the same column.

HTML::HTML5::Entities is a pure Perl, drop-in replacement for HTML::Entities, providing the character entities defined in HTML5.

Lingua::EN::PluralToSingular converts words denoting a plural in the English language into words denoting a singular noun.

The Lingua::EN::Sentence module contains the function get_sentences, which splits text into its constituent sentences, based on a regular expression and a list of abbreviations (built in and given). Seamus Venasse <svenasse@polaris.ca>

Squeeze English text to most compact format possibly so that it is barely readable. You should convert all text to lowercase for maximum compression, because optimizations have been designed mostly for uncapitalised letters. Seamus Venasse <svenasse@polaris.ca>

This is a simple module which makes an unscientific effort at summarizing English text. It recognizes simple patterns which look like statements, abridges them, and concatenates them into something vaguely resembling a summary. It needs more work on large bodies of text, but it seems to have a decent effect on small inputs at the moment. Seamus Venasse <svenasse@polaris.ca>

The module is a probability based, corpus-trained tagger that assigns POS tags to English text based on a lookup dictionary and probability values. The tagger determines appropriate tags based on conditional probabilities - it looks at the preceding tag to figure out what the appropriate tag is for the current word. Unknown words will be classified according to word morphology or can be set to be treated as nouns or other parts of speech. The tagger also recursively extracts as many nouns and noun phrases as it can, using a set of regular expressions.

Used in its basic form, this module provides an interface for generating basic HTML form elements much like HTML::StickyForms does. The main difference is HTML::SuperForm returns HTML::SuperForm::Field objects rather than plain HTML. This allows for more flexibilty when generating forms for a complex application. To get the most out of this module, use it as a base (Super) class for your own form object which generates your own custom fields. If you don't use it this way, I guess there's really nothing Super about it. Example are shown later in the document. The interface was designed with mod_perl and the Template Toolkit in mind, but it works equally well in any cgi environment.