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Sprachtechnologie für übersetzungsgerechtes Schreiben am Beispiel Deutsch, Englisch, Japanisch
(2009)
Wir [...] haben uns zur Aufgabe gesetzt, Wege zu finden, wie linguistisch basierte Software den Prozess des Schreibens technischer Dokumentation unterstützen kann. Dabei haben wir einerseits die Schwierigkeiten im Blick, die japanische und deutsche Autoren (und andere Nicht-Muttersprachler des Englischen) beim Schreiben englischer Texte haben. Besonders japanische Autoren haben mit Schwierigkeiten zu kämpfen, weil sie hochkomplexe Ideen in einer Sprache ausdrücken müssen, die von Informationsstandpunkt her sehr unterschiedlich zu ihrer Muttersprache ist. Andererseits untersuchen wir technische Dokumentation, die von Autoren in ihrer Muttersprache geschrieben wird. Obwohl hier die fremdsprachliche Komponente entfällt, ist doch auch erhebliches Verbesserungspotential vorhanden. Das Ziel ist hier, Dokumente verständlich, konsistent und übersetzungsgerecht zu schreiben. Der fundamentale Ansatz in der Entwicklung linguistisch-basierter Software ist, dass gute linguistische Software auf Datenmaterial basiert und sich an den konkreten Zielen der besseren Dokumentation orientiert.
Die Entwicklung eines individuellen Standards „vom grünen Tisch“ führt selten zu zufriedenstellenden Ergebnissen. Bei der automatischen Prüfung stellt man schnell fest, dass die „ausgedachten“ Regeln einer systematischen Anwendung nicht standhalten. Bei der Implementierung solcher Richtlinien stellt man fest, dass sie oft zu wenig konkret formuliert sind, wie z.B. „formulieren Sie Handlungsanweisungen knapp und präzise“. Wie jedoch kann ein Standard entwickelt werden, der zu einem Unternehmen, seiner Branche und Zielgruppen passt und für die automatische Prüfung implementiert werden kann? Sprachtechnologie hilft effizient bei der Entwicklung individueller Richtlinien. Durch Datenanalyse, Satzcluster und Parametrisierung entsteht ein textspezifischer individueller Standard. Ist damit aber der Gegensatz von Kreativität und Standardisierung aufgehoben?
This demo abstract describes the SmartWeb Ontology-based Information Extraction System (SOBIE). A key feature of SOBIE is that all information is extracted and stored with respect to the SmartWeb ontology. In this way, other components of the systems, which use the same ontology, can access this information in a straightforward way. We will show how information extracted by SOBIE is visualized within its original context, thus enhancing the browsing experience of the end user.
In this paper we describe SOBA, a sub-component of the SmartWeb multi-modal dialog system. SOBA is a component for ontologybased information extraction from soccer web pages for automatic population of a knowledge base that can be used for domainspecific question answering. SOBA realizes a tight connection between the ontology, knowledge base and the information extraction component. The originality of SOBA is in the fact that it extracts information from heterogeneous sources such as tabular structures, text and image captions in a semantically integrated way. In particular, it stores extracted information in a knowledge base, and in turn uses the knowledge base to interpret and link newly extracted information with respect to already existing entities.
The Deep Linguistic Processing with HPSG Initiative (DELH-IN) provides the infrastructure needed to produce open-source semantic transfer-based machine translation systems. We have made available a prototype Japanese-English machine translation system built from existing resources include parsers, generators, bidirectional grammars and a transfer engine.
This paper proposes an annotating scheme that encodes honorifics (respectful words). Honorifics are used extensively in Japanese, reflecting the social relationship (e.g. social ranks and age) of the referents. This referential information is vital for resolving zero
pronouns and improving machine translation outputs. Annotating honorifics is a complex task that involves identifying a predicate with honorifics, assigning ranks to referents of the
predicate, calibrating the ranks, and connecting referents with their predicates.
While the sortal constraints associated with Japanese numeral classifiers are wellstudied, less attention has been paid to the details of their syntax. We describe an analysis implemented within a broadcoverage HPSG that handles an intricate set of numeral classifier construction types and compositionally relates each to an appropriate semantic representation, using Minimal Recursion Semantics.
The research performed in the DeepThought project aims at demonstrating the potential of deep linguistic processing if combined with shallow methods for robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. On the basis of this approach, the feasibility of three ambitious applications will be demonstrated, namely: precise information extraction for business intelligence; email response management for customer relationship management; creativity support for document production and collective brainstorming. Common to these applications, and the basis for their development is the XML-based, RMRS-enabled core architecture framework that will be described in detail in this paper. The framework is not limited to the applications envisaged in the DeepThought project, but can also be employed e.g. to generate and make use of XML standoff annotation of documents and linguistic corpora, and in general for a wide range of NLP-based applications and research purposes.
Japanese is often taken to be strictly head-final in its syntax. In our work on a broad-coverage, precision implemented HPSG for Japanese, we have found that while this is generally true, there are nonetheless a few minor exceptions to the broad trend. In this paper, we describe the grammar engineering project, present the exceptions we have found, and conclude that this kind of phenomenon motivates on the one hand the HPSG type hierarchical approach which allows for the statement of both broad generalizations and exceptions to those generalizations and on the other hand the usefulness of grammar engineering as a means of testing linguistic hypotheses.
Hybrid robust deep and shallow semantic processing for creativity support in document production
(2004)
The research performed in the DeepThought project (http://www.project-deepthought.net) aims at demonstrating the potential of deep linguistic processing if added to existing shallow methods that ensure robustness. Classical information retrieval is extended by high precision concept indexing and relation detection. We use this approach to demonstrate the feasibility of three ambitious applications, one of which is a tool for creativity support in document production and collective brainstorming. This application is described in detail in this paper. Common to all three applications, and the basis for their development is a platform for integrated linguistic processing. This platform is based on a generic software architecture that combines multiple NLP components and on robust minimal recursive semantics (RMRS) as a uniform representation language.