Querying large treebanks : benchmarking GrETEL indexing

The amount of data that is available for research grows rapidly, yet technology to efficiently interpret and excavate these data lags behind. For instance, when using large treebanks for linguistic research, the speed of a query leaves much to be desired. GrETEL Indexing, or GrInding, tackles this issue. The idea behind GrInding is to make the search space as small as possible before actually starting the treebank search, by pre-processing the treebank at hand. We recursively divide the treebank into smaller parts, called subtree-banks, which are then converted into database files. All subtree-banks are organized according to their linguistic dependency pattern, and labeled as such. Additionally, general patterns are linked to more specific ones. By doing so, we create millions of databases, and given a linguistic structure we know in which databases that structure can occur, leading up to a significant efficiency boost. We present the results of a benchmark experiment, testing the effect of the GrInding procedure on the SoNaR-500 treebank

Improving the translation environment for professional translators

When using computer-aided translation systems in a typical, professional translation workflow, there are several stages at which there is room for improvement. The SCATE (Smart Computer-Aided Translation Environment) project investigated several of these aspects, both from a human-computer interaction point of view, as well as from a purely technological side. This paper describes the SCATE research with respect to improved fuzzy matching, parallel treebanks, the integration of translation memories with machine translation, quality estimation, terminology extraction from comparable texts, the use of speech recognition in the translation process, and human computer interaction and interface design for the professional translation environment. For each of these topics, we describe the experiments we performed and the conclusions drawn, providing an overview of the highlights of the entire SCATE project

Enriching a Descriptive Grammar with Treebank Queries

Abstract The Syntax of Dutch (SoD) is a descriptive and detailed grammar of Dutch, that provides data for many issues raised in linguistic theory. We present the results of a pilot project that investigated the possibility of enriching the online version of the text with links to queries that provide relevant results from syntactically annotated corpora

SPOD:Syntactic Profiler of Dutch

SPOD is a tool for Dutch syntax in which a given corpus is analysed according to a large number of predefined syntactic characteristics. SPOD is an extension of the PaQu (”Parse and Query”) tool (Odijk et al. 2017). SPOD is available for a number of standard Dutch corpora and treebanks.In addition, you can upload your own texts which will then be syntactically analysed. SPOD will run a potentially large number of syntactic queries in order to show a variety of corpus properties, such as the number of main and subordinate clauses, types of main and subordinate clauses, and their frequencies, average length of clauses (per clause type: e.g. relative clauses, indirect questions, finite complement clauses, infinitival clauses, finite adverbial clauses, etc.). Other syntactic constructions include comparatives, correlatives, various types of verb clusters, separable verb prefixes, depth of embedding etc.SPOD allows linguists to obtain a quick overview of the syntactic properties of texts, for instance with the goal to find interesting differences between text types, or between authors with different backgrounds or different age. In the paper, we describe the SPOD tool in some more detail, and we provide a case study, illustrating the type of investigations which are enabled andfacilitated by SPOD. Most of the syntactic properties are implemented in SPOD by means of relatively complicated XPath 2.0 queries, and as such SPOD also provides examples of relevant syntactic queries, which may otherwise be relatively hard to define for non-technical linguists