Application examples

We shall describe only a few of the many possible examples, leaving it to the reader to contrive others.

• Information Retrieval
  The grammar was developed for IR applications, in which the traditional keywords are to be replaced by frames obtained from phrases. All frames are first unnested, so that each document is represented by a bag of frames without nesting. The frames are also morphologically normalized, using a lemmatizer and the typing information provided. Furthermore, semantically related frames will be clustered together (see [Koster et al., 1999]).

• Information Analysis and Modelling
  An important step in most analysis techniques is to start out from an informal (i.e. verbal) description of the problem domain or the problem, and scan it for nouns and verbs: the nouns are candidate objects or classes and the verbs are candidate methods [Abbott, 1983]. Other elements, like the adjectives can also be used [Graham, 1994]. The HM frame representation obtained by using EP4IR can be used straight away for this purpose. The same technique can be used for the validation of an existing Object-Oriented Analysis model [Frederiks et al, 1996].

• Question answering system
  A question answering system of any kind will need more information than is included in the HM frames, e.g. quantifiers and determiners. Of course the grammar does already recognize these constructs, so by modifying three or four lines in the transduction they will also be expressed. Luckily, the grammar already knows how to parse questions.

Feel free to use the AGFL system for your purposes according to the GPL/LGPL license. Let us know if you have a nice application. For more complicated projects you might consider collaborating with the authors of this paper.