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Integrated Linguistic Annotation Models and Their Application in the Domain of Antecedent Detection
(2011)
Seamless integration of various, often heterogeneous linguistic resources in terms of their output formats and a combined analysis of the respective annotation layers are crucial tasks for linguistic research. After a decade of concentration on the development of formats to structure single annotations for specific linguistic issues, in the last years a variety of specifications to store multiple annotations over the same primary data has been developed. The paper focuses on the integration of the knowledge resource logical document structure information into a text document to enhance the task of automatic anaphora resolution both for the task of candidate detection and antecedent selection. The paper investigates data structures necessary for knowledge integration and retrieval.
Different Views on Markup
(2010)
In this chapter, two different ways of grouping information represented in document markup are examined: annotation levels, referring to conceptual levels of description, and annotation layers, referring to the technical realisation of markup using e.g. document grammars. In many current XML annotation projects, multiple levels are integrated into one layer, often leading to the problem of having to deal with overlapping hierarchies. As a solution, we propose a framework for XML-based multiple, independent XML annotation layers for one text, based on an abstract representation of XML documents with logical predicates. Two realisations of the abstract representation are presented, a Prolog fact base format together with an application architecture, and a specification for XML native databases. We conclude with a discussion of projects that have currently adopted this framework.
This article shows that the TEI tag set for feature structures can be adopted to represent a heterogeneous set of linguistic corpora. The majority of corpora is annotated using markup languages that are based on the Annotation Graph framework, the upcoming Linguistic Annotation Format ISO standard, or according to tag sets defined by or based upon the TEI guidelines. A unified representation comprises the separation of conceptually different annotation layers contained in the original corpus data (e.g. syntax, phonology, and semantics) into multiple XML files. These annotation layers are linked to each other implicitly by the identical textual content of all files. A suitable data structure for the representation of these annotations is a multi-rooted tree that again can be represented by the TEI and ISO tag set for feature structures. The mapping process and representational issues are discussed as well as the advantages and drawbacks associated with the use of the TEI tag set for feature structures as a storage and exchange format for linguistically annotated data.