Daniela Goecke

Web-based Annotation of Anaphoric Relations and Lexical Chains

Annotating large text corpora is a time-consuming effort. Although single-user annotation tools are available, web-based annotation applications allow for distributed annotation and file access from different locations. In this paper we present the web-based annotation application Serengeti for annotating anaphoric relations which will be extended for the annotation of lexical chains.

Markup Infrastructure for the Anaphoric Bank: Supporting Web Collaboration

Modern NLP systems rely either on unsupervised methods, or on data created as part of governmental initiatives such as MUC, ACE, or GALE. The data created in these efforts tend to be annotated according to task-specific schemes. The Anaphoric Bank is an attempt to create large quantities of data annotated with anaphoric information according to a general purpose and linguistically motivated scheme. We do this by pooling smaller amounts of data annotated according to rich schemes that are by and large compatible, and by taking advantage of Web collaboration. In this chapter we discuss the markup infrastructure that underpins the two modalities of Web collaboration in the project: expert annotation and game-based annotation.

Multidimensional markup and heterogeneous linguistic resources

The paper discusses two topics: firstly an approach of using multiple layers of annotation is sketched out. Regarding the XML representation this approach is similar to standoff annotation. A second topic is the use of heterogeneous linguistic resources (e.g., XML annotated documents, taggers, lexical nets) as a source for semi-automatic multi-dimensional markup to resolve typical linguistic issues, dealing with anaphora resolution as a case study.1

Integrated linguistic annotation models and their application in the domain of antecedent detection

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.