Formal and Relational Concept Analysis have already been used for applications in various subject areas. They are applicable to linguistics in several ways. First, they can facilitate the formalization of linguistic items by restricting lexical data to fixed contexts and specifying the role of each item in the context. While constructing formal contexts, the linguist has to determine if the formal objects are denotata of word forms, word forms or disambiguated word forms (Priss, in prep.2). The formal attributes can be attributes of denotata or connotational attributes. Depending on the selection of objects and attributes, the resulting formal concepts can represent denotative concepts, meta-concepts, word concepts or others.
Second, Woods' idea of inheritance of semantic relations (for example, from subconcepts to superconcepts) can be formalized, further investigated, and formally proved in the framework of Relational Concept Analysis (Priss, in prep.1). This can be applied to any semantic network that has hierarchical relations. Third, irregularities in the implementation of the semantic relations of a lexical database can be found and corrected. This is shown for the lexical database, WordNet, by Priss (in prep.3). Fourth, in this paper formal properties of semantic relations are used to obtain classificational attributes. This is demonstrated using the quantificational tags of the meronymy relation.
Lattices are effectively visualized by line diagrams Each object g labels the concept \gamma g in the line diagram that is the smallest concept the object belongs to. Dually, an attribute m labels \mu m the largest concept it belongs to. The advantage of the lattice representation is that the similarity of the `relation families' does not have to be calculated using statistical methods as in Chaffin & Herrmann's paper. But the similarities of the relation families to each other can be examined by investigating the lattice diagram. It becomes, for example, obvious that `functional object' and `functional location' are not properly discriminated. Maybe `functional location' should also have the relation element `locative'. It can be observed that `group' is a subconcept of `collection', because a `group' has all the relation elements of a `collection' but furthermore it has the relation element `social'. These examples show that the lattice representation can serve as the basis for a scientific discussion on subjects whose structure would not be transparent otherwise.
The table contains the attempt to classify the meronymy relation by using quantificational tags. The examples are not complete. Missing combinations do not suggest that those examples do not exist, but that the author has not found them yet.
The first rows of the table show that the quantificational tags depend on the level of abstraction of the objects (compare, for example, meat/sausage and sausage meat/sausage). Furthermore, although meronymy relations with different relational components can share the same tags, each class of relational components tends to prefer a special tag. Therefore the tags can be a basis of a classification. The resulting classes differ from the four meronymy models of Iris et al., which distinguish membership, segmented whole, subset, and functional components. Here membership and segmented whole are in some cases closer together (compare human/citizenship and chapter/book). For the object/object relations, which correspond to the functional components, this classification seems to be the most unsatisfactory. For example, Chaffin & Herrmann's component/integral object, topological part/object, time/time, and place/area are all subsumed under object/object. Hopefully there will be a combination of research on tags and relational components in the future.
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