Digital Humanities Abstracts

“A Formal Model for Lexical Information”
Nancy Ide Vassar College, USA Adam Kilgarriff ITRI Brighton, UK Laurent Romary LORIA/CNRS, France

1. Introduction

The structure and content of lexical information has been explored in considerable depth in the past, primarily in order to determine a common model that can serve as a basis for encoding schemas and/or database models. For the most part, descriptions of lexical structure have been informed by the format of printed documents (e.g., print dictionaries), which varies considerably over documents produced by different publishers and for different purposes, together with the requirements for instantiation in some encoding format (principally, SGML). However, the constraints imposed by these formats interfere with the development of a model that fully captures the underlying structure of lexical information. As a result, although schemas such as those provided in the TEI Guidelines exist, they do not provide a satisfactorily comprehensive and unique description of lexical structure and content. We believe that in order to develop a concrete and general model of lexical information, it is essential to distinguish between the formal model itself and the encoding or database schema that may ultimately instantiate it. That is, it is necessary to consider, in the abstract, the form and content of lexical information independent of requirements and/or limitations imposed its ultimate representation as an encoded or printed object. This is especially important since these eventual representations will vary from one application to another; in particular, lexical information may be encoded not only for the purposes of publishing in print or electronic form, but also for creating computational lexicons, terminology banks, etc. for use in natural language processing applications. It is therefore essential to develop a model that may be subsequently transformed into a variety of alternative formats. In this paper, we outline a formal model for lexical information that describes (a) the structure of this information, (b) the information associated with this structure at various levels, and (c) a system of inheritance of information over this structure. We then show how the structure may be instantiated as a document encoded using the Extended Markup Language (XML). Using the transformation language provided by the Extensible Style Language (XSL), we then demonstrate how the original XML instantiation may be transformed into other XML documents according to any desired configuration (including omission) of the elements in the original. Because of its generality, we believe our model may serve as a basis for representing, combining, and extracting information from dictionaries, terminology banks, computational lexicons, and, more generally, a wide variety of structured and semi-structured document types.

2. Overview of the theoretical model

The underlying structure of lexical information can be viewed as embedded partitions of a lexicon, in which no distinction is made among embedded levels. A model of lexical information can be thus described as a recursive structure comprised, at each level, of one or more nodes. This structure is most easily visualized as a tree, where each node may have zero or more children. That is, at any level n, a node is either a leaf (i.e., with no children) or can be decomposed as:T=[T1, T2, ..., Tn]where each Ti is a node at level n+1. Properties may be attached to any node in the structure with the prop predicate: PROP(T,P)indicates that the property P is attached to node T. Properties are associated with nodes either by explicit assignment, or they may be inherited from the parent node. The object of our model is to identify the ways in which properties are propagated through levels of structure. For this purpose, we consider properties to be Feature-Value pairs expressed as terms of the form FEAT(F,V), where F and V are tokens designating a feature (e.g., POS) and a value. In the simplest case, values are atomic (e.g., NOUN) but may also consist of sets of feature-value pairs. This representation is consistent with the base notation associated with feature structures, a common framework for representing linguistic information.

3. Propagating information across levels

We define three types of features:
  • Cumulative features that may take more than one value and may be thus inherited and combined along the structure. For example, for a cumulative feature DOMAIN, if the property FEAT(DOMAIN,NAVIGATION) is associated with a node at level n and FEAT(DOMAIN,LAW) is associated with its child at level n+1, by inheritance the node at level n+1 will be assigned the property FEAT(DOMAIN,NAVIGATION + LAW).
  • Overwriting features that take only one value at a time. This implies that only one instance of an overwriting feature may appear at a given node and that the corresponding properties are propagated along the structure unless and until a new value is specified for that feature. In such a case, the new value "overwrites" the earlier one and is subsequently propagated to nodes in its subtrees.
  • Local features, which apply only at the node with which they are associated; i.e., they are not propagated through the structure. Cross-references are an example of a local feature, since they apply only to the level of description with which they are directly associated.
The full paper will provide details of this formalism.

4. Creating representations

Lexical information can be represented as a tree structure reflecting, in large part, the natural hierarchical organization of entries found in printed dictionaries. This hierarchical organization (e.g., division into homographs, senses, sub-senses, etc.) enables information to be applied over all sub-levels in the hierarchy, thus eliminating the need to re-specify common information. For example, consider the following definition from the Collins English Dictionary (CED):
EX.1: overdress
overdress vb. (zzzz) 1. To dress (oneself or another) too elaborately or finely. ~n. (yyyy) 2. A dress that may be worn over a jumper, blouse, etc.
This information can be represented in tree form as follows :
[ orth : overdress] [ pos : verb pron : zzzz def: To dress (oneself or another) too elaborately or finely] [ pos : noun pron : yyyy def : A dress that may be worn over a jumper, blouse, etc.]
Each node in the tree represents a partition of the information in the entry, and information is inherited over sub-trees. Thus in this example, the orthographic form "overdress" appears at the top node and applies to the entire entry; the entry is then partitioned into two sub-trees, for verb and noun, each of which is associated with specific information about part of speech, pronunciation, and definition. The final paper will provide similar examples from dictionaries as well as terminological data banks.

5. Extracting information from the tree

We define a tree traversal as any path starting at the root of the tree and following, at each node, a single child of that node. A full traversal is a path from the root to any leaf; a partial traversal extends from the root to any node in one of its subtrees. As a tree is traversed, each node is associated with a set of features including: (a) features associated with the node during tree creation, and (b) features determined by applying the rules for propagating overwriting, cumulative, and local features. Thus, at any node, all applicable information is available for some unique partition of the lexical space. Nodes near the top of the tree represent very broad categories of partition; leaf nodes are associated with information for the most specific usage of the entry.

6. Encoding the information in XML

We define an XML encoding format for the structures described above:


<struct> represents a node in the tree. <struct> elements may be recursively nested at any level to reflect the structure of the corresponding tree. <struct> is the only element in the encoding scheme that corresponds to the tree structure; all other elements provide information associated with a specific node. <alt> alternatives are bracketed in parallel <alt> elements, which may appear within any <struct>. <brack> is a general-purpose bracketing element to group associated features. Base elements corresponding to various features, such as (for dictionaries) orth, pron, hyph, syll, stress, pos, gen, case, number, gram, tns, mood, usg, time, register, geo, domain, style, def, eg, etym, xr, trans, and itype, (analogous to dictionary elements defined in the TEI Guidelines.) >


Attributes are used to provide information specific to the element on which they appear and are not inherited in a tree traversal. The following shows the corresponding XML encoding for "overdress":
<struct> <orth>overdress</> <struct> <pos>verb</> <pron>zzzz</> <def> To dress (oneself or another) too elaborately or finely</></> <struct> <pos>noun</> <pron>yyyy</> <def> A dress that may be worn over a jumper, blouse, etc.</></></>

7. Transforming the XML document

The Extensible Style Language (XSL) is a part of the XML framework that enables transformation of XML documents into other XML documents. The best-known use of XSL is the formatting of documents for display on web browsers. However, XSL also provides a powerful transformation language that can be used to convert an XML document describing lexical information by selecting, rearranging, and adding information to it. Thus, a document encoded according to the specifications outlined in the previous section can be manipulated to serve any application that relies on part or all of its contents. The current version of the XSL transformation language is available at <>. Lack of space prevents providing examples; the final paper will include these.