This paper reports on the TIGER Treebank, a corpus of currently 40,000 syntactically annotated German newspaper sentences. We describe what kind of information is encoded in the treebank and introduce the different representation formats that are used for the annotation and exploitation of the treebank. We explain the different methods used for the annotation: interactive annotation, using the tool ANNOTATE, and LFG parsing. Furthermore, we give an account of the annotation scheme used for the TIGER treebank. This scheme is an extended and improved version of the NEGRA annotation scheme and we illustrate in detail the linguistic extensions that were made concerning the annotation in the TIGER project. The main differences are concerned with coordination, verb-subcategorization, expletives as well as proper nouns. In addition, the paper also presents the query tool TIGERSearch that was developed in the project to exploit the treebank in an adequate way. We describe the query language which was designed to facilitate a simple formulation of complex queries; furthermore, we shortly introduce TIGER in, a graphical user interface for query input. The paper concludes with a summary and some directions for future work.

This article provides an extensive overview of the literature related to the phenomenon of non-nominal-antecedent anaphora (also known as abstract anaphora or discourse deixis), a type of anaphora in which an anaphor like “that” refers to an antecedent (marked in boldface) that is syntactically non-nominal, such as the first sentence in “It’s way too hot here. That’s why I’m moving to Alaska.” Annotating and automatically resolving these cases of anaphora is interesting in its own right because of the complexities involved in identifying non-nominal antecedents, which typically represent abstract objects such as events, facts, and propositions. There is also practical value in the resolution of non-nominal-antecedent anaphora, as this would help computational systems in machine translation, summarization, and question answering, as well as, conceivably, any other task dependent on some measure of text understanding. Most of the existing approaches to anaphora annotation and resolution focus on nominal-antecedent anaphora, classifying many of the cases where the antecedents are syntactically non-nominal as non-anaphoric. There has been some work done on this topic, but it remains scattered and difficult to collect and assess. With this article, we hope to bring together and synthesize work done in disparate contexts up to now in order to identify fundamental problems and draw conclusions from an overarching perspective. Having a good picture of the current state of the art in this field can help researchers direct their efforts to where they are most necessary. Because of the great variety of theoretical approaches that have been brought to bear on the problem, there is an equally diverse array of terminologies that are used to describe it, so we will provide an overview and discussion of these terminologies. We also describe the linguistic properties of non-nominal-antecedent anaphora, examine previous annotation efforts that have addressed this topic, and present the computational approaches that aim at resolving non-nominal-antecedent anaphora automatically. We close with a review of the remaining open questions in this area and some of our recommendations for future research.

We present CorA, a web-based annotation tool for manual annotation of historical and other non-standard language data. It allows for editing the primary data and modifying token boundaries during the annotation process. Further, it supports immediate retraining of taggers on newly annotated data.

We present a new multi-layered annotation scheme for orthographic errors in freely written German texts produced by primary school children. The scheme is closely linked to the German graphematic system and defines categories for both general structural word properties and errorrelated properties. Furthermore, it features multiple layers of information which can be used to evaluate an error. The categories can also be used to investigate properties of correctly-spelled words, and to compare them to the erroneous spellings. For data representation, we propose the XML-format LearnerXML.

In this paper, we present first results from annotating abstract (discourse-deictic) anaphora in German. Our annotation guidelines provide linguistic tests for identifying the antecedent, and for determining the semantic types of both the antecedent and the anaphor. The corpus consists of selected speaker turns from the Europarl corpus. To date, 100 texts have been annotated according to these guidelines. The annotations show that anaphoric personal and demonstrative pronouns differ with respect to the distance to their antecedents. A semantic analysis reveals that, contrary to suggestions put forward in the literature, referents of anaphors do not tend to be more abstract than the referents of their antecedents.Keywords Abstract anaphora Á Abstract entities Á Coreference annotation Á Semantic annotation 1 Introduction