Publication
Proceedings of the COLING '00 Workshop on Semantic Annotation and Intelligent Content, August 5-6
Martin Kay (Hrsg.)
International Conference on Computational Linguistics (COLING), 2000.
Abstract
SEMANTIC ANNOTATION is augmentation of data to facilitate automatic recognition of the underlying semantic structure. A common practice in this respect is labeling of documents with thesaurus classes for the sake of document classification and management. In the medical domain, for instance, there is a long-standing tradition in terminology maintenance and annotation/classification of documents using standard coding systems such as ICD, MeSH and the UMLS meta-thesaurus. Semantic annotation in a broader sense also addresses document structure (title, section, paragraph, etc.), linguistic structure (dependency, coordination, thematic role, co-reference, etc.), and so forth. In NLP, semantic annotation has been used in connection with machine-learning software trainable on annotated corpora for parsing, word-sense disambiguation, co-reference resolution, summarization, information extraction, and other tasks. A still unexplored but important potential of semantic annotation is that it can provide a common I/O format through which to integrate various component technologies in NLP and AI such as speech recognition, parsing, generation, inference, and so on. INTELLIGENT CONTENT is semantically structured data that is used for a wide range of content-oriented applications such as classification, retrieval, extraction, translation, presentation, and question-answering, as the organization of such data provides machines with accurate semantic input to those technologies. Semantically annotated resources as described above are typical examples of intelligent content, whereas another major class includes electronic dictionaries and inter-lingual or knowledge-representation data. Some ongoing projects along these lines are GDA (Global Document Annotation), UNL (Universal Networking Language) and SHOE (Simple HTML Ontology Extension), all of which aim at motivating people to semantically organize electronic documents in machine-understandable formats, and at developing and spreading content-oriented application technologies aware of such formats. Along similar lines, MPEG-7 is a framework for semantically annotating audiovisual data for the sake of content-based retrieval and browsing, among others. Incorporation of linguistic annotation into MPEG-7 is in the agenda, because linguistic descriptions already constitute a main part of existing metadata. In short, semantic annotation is a central, basic technology for intelligent content, which in turn is a key notion in systematically coordinating various applications of semantic annotation. In the hope of fueling some of the developments mentioned above and thus promoting the linkage between basic researches and practical applications, the workshop invites researchers and practitioners from such fields as computational linguistics, document processing, terminology, information science, and multimedia content, among others, to discuss various aspects of semantic annotation and intelligent content in an interdisciplinary way.