Meaning and interpretation of concurrent markup

Meaning and interpretation of concurrent markup

Andreas
Witt

Universität Bielefeld
Andreas.Witt@uni-bielefeld.de

2002

University of Tübingen

Tübingen

ALLC/ACH 2002

editor

Harald
Fuchs

encoder

Sara
A.
Schmidt

Introduction
The difficulty of annotating not hierarchically structured text with
SGML-based mark-up languages is a problem that has often been addressed.
Renear et al. (1996) discuss one of the basic assumptions about the
structure of text data: the "OHCO-thesis", which states that text consists
of an ordered hierarchy of content objects, and show that this assumption
cannot be upheld consistently: A number of texts contradict this
OHCO-thesis.
The options to represent data which correspond to different structural
hierarchies are discussed in detail by the TEI (see Barnard et al. 1995).
One type of annotation mentioned by the TEI-guidelines consists of
separately annotating the original data according to different document
grammars. "The advantages of this method of markup are that each way of
looking at the information is explicitly represented in the data, and may be
processed in straightforward ways, without requiring complex methods of
disentangling information relevant to one view from information relevant
only to other views." (Sperberg-McQueen & Burnard 1994, p.775f.) The
problem, however, is that separate annotations do not allow for establishing
relations between the annotation tiers. It will be shown that a model for
the meaning and interpretation of documents, marked-up once, can be extended
to documents concurrently marked-up with several annotations.The
work presented here is described in more detail in Witt
(2002).

Model of representation
The model of representing complex structured text is itself based on the data
to be structured. This data can be annotated according to specific document
grammars. For a simple case there is one document grammar and one
annotation. This means all SGML documents and all valid XML documents are
represented by this model. In addition to this standard representation every
document can be structured according to further document grammars. The
maximal number of annotations is not restricted, so that the model permits a
steady expansion of the annotations which are used. Therefore, the model can
be viewed as an open model. As a result the annotated text data fuses
different levels of annotation together.
As a prerequisite the preparation of the data must be done in a way that a
separate annotation of relevant phenomena is possible. The data which will
be annotated is categorized as having a status of primary data. The primary
data consists of the yet to be annotated text. Accordingly, the mark-up will
be categorized as secondary data or meta-data.The terminus
"meta-data" is preferred by the author, because "secondary data"
presupposes a characterization as less important data. However,
"meta-data" is far from being the ideal term: it causes an ambiguity,
since it is also used for the information typically contained in the
headers of annotated documents. The primary data is used in two
ways: On the one hand, the primary data is the subject of several (possible)
annotations, on the other hand it forms a link between the levels of
annotation. It is important to note that the second way of using the primary
data allows for linking the independent annotations without introducing
explicit links.
After the stipulation of the primary data individual document grammars can be
developed and applied which each pertain to a single level of annotation.
For the annotation of linguistic data this could be e.g. the level of
morphology, the level of syllable structures, a level of syntactic
categories (e.g. noun, verb), a level of syntactic functions (e.g. subject,
object), or a level of semantic roles (e.g. agent, instrument).
As already mentioned this annotation technique data allows for the
introduction of an unlimited number of concurrent annotations, but there
exists a constraint: when designing the document grammar it is necessary to
consider that the primary data is the link between all layers of annotation.
This has a direct consequence for the modelling process: Even if parts of
the primary data are irrelevant for one of the tiers of description, the
data must exist as primary data in the annotation. This contradiction can be
solved by introducing a special mark for this irrelevant primary data in the
document grammar according to the phenomena. This mark allows one to
represent the corresponding passages as primary data in a technical way.
Such a mark can be done for example by using the element <ignore>. While interpreting the
distinguished data these marked sections will be filtered out. Durand et al.
(1996) already discussed a similar solution where a classification on a more
abstract level of representation should happen.
The compilation of document grammars which are used for different
annotations, can be seen as a pool of individual units or as a collectively
structured source of knowledge. Not only the structure of document grammars,
but also the schema language used (e.g. DTD, XSchema) are irrelevant to the
process of annotations.

Knowledge representation of annotated text
In general, annotated text consists of content and annotations. Annotations
are used on a syntactical level. Therefore they are used for assigning a
meaning to (parts of) a document. While developing a document grammar the
focus should be centred on the content. This point of view is expressed by
Sperberg-McQueen, Huitfeldt and Renear (2000). They show how knowledge which
is syntactically coded into text by annotations can be extracted by
knowledge inference. After summarizing this approach, it will be shown, how
this technique can be expanded so that it can be used for inferences of
separately annotated and implicitly linked documents - documents marked-up
according to different document grammars.

Documents
Sperberg-McQueen et al. (2000) regard annotated documents as a compilation of
knowledge which can be represented and can be used for inference.
Illustrating their approach they use the programming language "Prolog" to
represent this knowledge. A XML-Document without cross relations can be
represented as a tree. A representation of annotated text in Prolog looks
like the following:
node([x, y, z], element(gi)).

attr([x, y, z],attr-name, 'att-value').
A predicate with two arguments, called node (or
short notation in Prolog node/2), is used. The
first argument is a list of digits to identify each node of the tree
representation of documents. The second argument is more complex. It
consists of the functor element or pcdata and an argument for the name of the
element or the textual content. Furthermore, a predicate of three arguments
called attr/3 is used for representing
attributes. Attributes are also related to nodes (argument 1). They have a
name (argument 2) and a value (argument 3). Such a representation of a
document is a very good basis for automatic inference of relations which
exist between the nodes. If e.g. infer/2 is
called with an address, all active features can be printed out:
infer(Property,[x, y, z]).

Property = a;
If infer/2 is called with a concrete feature
and a variable at the place of the address, all locations are printed out
which apply to these features.
Other frameworks for knowledge representation of annotated documents also
exist. Welty and Ide (1999) introduced an approach, where the knowledge of
documents is pasted into a knowledge representation system. However, so far
it has not been shown how to use differently annotated documents as a base
for inferences.

Relations between separate annotations
The described model of knowledge representation can only be used for single
documents. However, it will be shown, that this model can easily be
expanded, so that it is applicable for the inference of relations between
several separately annotated XML-documents with the same primary data.
In order to use the model for several different annotations the
representation of an absolute system of references must be introduced. This
absolute reference system is already given in the data: the parts of text
which are saved as "PCDATA", i.e. the primary data as defined above, is
ideally suited for this task. This means that the string which is identical
in all documents serves as the absolute system of references.
The primary data forms a string of a fixed length. The representation of the
annotation tiers is an absolute basis of relations. This basis must renounce
the predicates node/2 and attr/3 in favour of the predicates node/5 and attr/6. The three
additional arguments are used for the reference on the level of annotation
(comparable to the concept of namespaces in XML), for marking the start and
the end of the annotated textual content.
The extension of the original model in this way allows for inferences of
relations between different concurrent annotations, e.g. regarding the
separate annotation of morphemes and syllables might show that these units
are not compatible.Other relations of concurrent markup can be,
for example, compatibility, identity, and inclusion. Since the
arguments originally introduced are reused, all the inferences of the
original model are still possible.

Advantages and Perspectives
The outlined architecture has many advantages. The model allows for
structuring text according to multiple concurrent document grammars without
workarounds. Furthermore additional annotations can be subsequently
included, without changing already established annotations. The annotations
are on the one hand independent of each other, on the other hand they are
interrelated via the text, allowing for the inference of relations between
different levels of annotation. The final advantage to be mentioned is that
the compatibility of several or all annotations used can be proven
automatically. This can be done using a technique originally developed
within linguistics, namely unification.

Bibliography

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Barnard
et al
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Véronis

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David
Durand

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DeRose

What Should Markup Really Be?

ALLC/ACH 1996

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Ide

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Renear

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Mylonas

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Durand

Refining Our Notion of What Text Really Is: The Problem
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Burnard

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Meaning and interpretation of Markup

Markup Languages

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Chris
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Nancy
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Andreas
Witt

Multiple Informationsstrukturierung mit
Auszeichnungssprachen. XML-basierte Methoden und deren Nutzen für
die Sprachtechnologie

Ph.D. thesis

Bielefeld University