Feature structures group phonemes with binary values, represented by attribute-value matrices or directed acyclic graphs. They are used in grammatical studies and text coding initiatives, but have limitations in producing generalizations and containing all possible values. A solution is to include a third column for types to organize features hierarchically.
The feature structure is used to group phonemes and to give them binary values. The idea was first proposed by Roman Jacobson in 1949. It is used as part of grammatical studies, especially studies of the structure of language and grammatical interactions. In essence, a feature structure is an attempt to understand the structure of the grammar and create a working system for representing how different elements of the grammar interact.
Each feature structure is represented using an attribute-value matrix (AVM). This is a set of terms and symbols enclosed in parentheses. It almost looks like the grammatical equivalent of a mathematical formula.
The AVMs are divided into two columns. The left column represents characteristics such as category and agreement. The right column represents the sub-characteristics of each characteristic such as gender and number. Each sub-characteristic in the right column is assigned a value. For gender, the value would be masculine, feminine, or neuter, and for number, it would be single or plural.
An alternative method of representing a structure of features is a directed acyclic graph (DAG). The graph starts with a point, also called a node. Each feature departs from the node along a curved arrow. Each feature can then be broken down into sub-features. Subfeatures terminate in another node that contains the value of the subfeature.
An example of this would be a node leading to the chord function leading to the person subcharacteristic and a value of 3rd. Represents a sentence said in the third person. In languages where gender is an important feature, the feature arrow might split into gender and person and would result in two values at the end. For example, this could mean third person and woman.
Unification in a feature tree means that two features can be split into sub-features, which then merge. Mergers within unified feature strands are of equal value and are best represented using a DAG rather than an AVM. In addition to unifying feature structures, attempts at unification can also demonstrate that some structures are incompatible.
Feature structures are used for text coding initiatives (TEI). These create markup schemes for linguists. Such schemes can then be used to parse or interpret encrypted and scrambled texts.
There are two main problems with using a feature structure. First, feature structures produce many generalizations. Second, they and unifying structures cannot contain all possible values in a language.
A suggested solution to this problem is to include a third column or main branch called types. Each type would organize features into appropriate sections or classes. In this way, the characteristics would be adjusted and so would the values that each characteristic can take. Types would work in a hierarchical system to regulate feature interactions.
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