This paper presents an analysis of annotation using an automatic pre-annotation for a mid-level annotation complexity task - dependency syntax annotation. It compares the annotation efforts made by annotators using a pre-annotated version (with a high-accuracy parser) and those made by fully manual annotation. The aim of the experiment is to judge the final annotation quality when pre-annotation is used. In addition, it evaluates the effect of automatic linguistically-based (rule-formulated) checks and another annotation on the same data available to the annotators, and their influence on annotation quality and efficiency. The experiment confirmed that the pre-annotation is an efficient tool for faster manual syntactic annotation which increases the consistency of the resulting annotation without reducing its quality.

Recently, many corpora have been developed that contain multiple annotations of various linguistic phenomena, from morphological categories of words through the syntactic structure of sentences to discourse and coreference relations in texts. Discussions are ongoing on an appropriate annotation scheme for a large amount of diverse information. In our contribution we express our conviction that a multilayer annotation scheme offers to view the language system in its complexity and in the interaction of individual phenomena and that there are at least two aspects that support such a scheme: (i) A multilayer annotation scheme makes it possible to use the annotation of one layer to design the annotation of another layer(s) both conceptually and in a form of a pre-annotation procedure or annotation checking rules. (ii) A multilayer annotation scheme presents a reliable ground for corpus studies based on features across the layers. These aspects are demonstrated on the case of the Prague Dependency Treebank. Its multilayer annotation scheme withstood the test of time and serves well also for complex textual annotations, in which earlier morpho-syntactic annotations are advantageously used. In addition to a reference to the previous projects that utilise its annotation scheme, we present several current investigations.

We present a richly annotated and genre-diversified language resource, the Prague Dependency Treebank-Consolidated 1.0 (PDT-C 1.0), the purpose of which is - as it always been the case for the family of the Prague Dependency Treebanks - to serve both as a training data for various types of NLP tasks as well as for linguistically-oriented research. PDT-C 1.0 contains four different datasets of Czech, uniformly annotated using the standard PDT scheme (albeit not everything is annotated manually, as we describe in detail here). The texts come from different sources: daily newspaper articles, Czech translation of the Wall Street Journal, transcribed dialogs and a small amount of user-generated, short, often non-standard language segments typed into a web translator. Altogether, the treebank contains around 180,000 sentences with their morphological, surface and deep syntactic annotation. The diversity of the texts and annotations should serve well the NLP applications as well as it is an invaluable resource for linguistic research, including comparative studies regarding texts of different genres. The corpus is publicly and freely available.

We present coreference annotation on parallel Czech-English texts of the Prague Czech-English Dependency Treebank (PCEDT). The paper describes innovations made to PCEDT 2.0 concerning coreference, as well as coreference information already present there. We characterize the coreference annotation scheme, give the statistics and compare our annotation with the coreference annotation in Ontonotes and Prague Dependency Treebank for Czech. We also present the experiments made using this corpus to improve the alignment of coreferential expressions, which helps us to collect better statistics of correspondences between types of coreferential relations in Czech and English. The corpus released as PCEDT 2.0 Coref is publicly available.

We introduce a substantial update of the Prague Czech-English Dependency Treebank, a parallel corpus manually annotated at the deep syntactic layer of linguistic representation. The English part consists of the Wall Street Journal (WSJ) section of the Penn Treebank. The Czech part was translated from the English source sentence by sentence. This paper gives a high level overview of the underlying linguistic theory (the so-called tectogrammatical annotation) with some details of the most important features like valency annotation, ellipsis reconstruction or coreference.

In this paper, we present several ways to measure and evaluate the annotation and annotators, proposed and used during the building of the Czech part of the Prague Czech-English Dependency Treebank. At first, the basic principles of the treebank annotation project are introduced (division to three layers: morphological, analytical and tectogrammatical). The main part of the paper describes in detail one of the important phases of the annotation process: three ways of evaluation of the annotators - inter-annotator agreement, error rate and performance. The measuring of the inter-annotator agreement is complicated by the fact that the data contain added and deleted nodes, making the alignment between annotations non-trivial. The error rate is measured by a set of automatic checking procedures that guard the validity of some invariants in the data. The performance of the annotators is measured by a booking web application. All three measures are later compared and related to each other.