The DeepThought Core Architecture Framework

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

Hybrid robust deep and shallow semantic processing for creativity support in document production

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

An integrated architecture for shallow and deep processing

We present an architecture for the integration of shallow and deep NLP components which is aimed at flexible combination of different language technologies for a range of practical current and future applications. In particular, we describe the integration of a high-level HPSG parsing system with different high-performance shallow components, ranging from named entity recognition to chunk parsing and shallow clause recognition. The NLP components enrich a representation of natural language text with layers of new XML meta-information using a single shared data structure, called the text chart. We describe details of the integration methods, and show how information extraction and language checking applications for realworld German text benefit from a deep grammatical analysis

Corpora and evaluation tools for multilingual named entity grammar development

We present an effort for the development of multilingual named entity grammars in a unification-based finite-state formalism (SProUT). Following an extended version of the MUC7 standard, we have developed Named Entity Recognition grammars for German, Chinese, Japanese, French, Spanish, English, and Czech. The grammars recognize person names, organizations, geographical locations, currency, time and date expressions. Subgrammars and gazetteers are shared as much as possible for the grammars of the different languages. Multilingual corpora from the business domain are used for grammar development and evaluation. The annotation format (named entity and other linguistic information) is described. We present an evaluation tool which provides detailed statistics and diagnostics, allows for partial matching of annotations, and supports user-defined mappings between different annotation and grammar output formats

D=4, N=1 Supersymmetric Henneaux-Knaepen Models

We construct N=1 supersymmetric versions of four-dimensional Freedman-Townsend models and generalizations thereof found recently by Henneaux and Knaepen, with couplings between 1-form and 2-form gauge potentials. The models are presented both in a superfield formulation with linearly realized supersymmetry and in WZ gauged component form. In the latter formulation the supersymmetry transformations are nonlinear and do not commute with all the gauge transformations. Among others, our construction yields N=1 counterparts of recently found N=2 supersymmetric gauge theories involving vector-tensor multiplets with gauged central charge.Comment: 20 pages, uses amsmath.st

Masses and Dualities in Extended Freedman-Townsend Models

We consider some generalizations of Freedman-Townsend models of self-interacting antisymmetric tensors, involving couplings to further form fields introduced by Henneaux and Knaepen. We show how these fields can provide masses to the tensors by means of the Stueckelberg mechanism and implement the latter in four-dimensional N=1 superspace. The duality properties of the form fields are studied, and the paradoxical situation of a duality between a free and an interacting theory is encountered.Comment: 5 pages; v2: minor changes, references added; v3: some clarifications, published version; v4: generalized decoupling condition

An HSPG-to-CFG Approximation of Japanese

We present a simple approximation method for turning a Head-Driven Phrase Structure Grammar into a context-free grammar. The approximation method can be seen as the construction of the least fixpoint of a certain monotonic function. We discuss an experiment with a large HPSG for Japanese