Johannes Dellert


Welcome to my website! I am a computational linguist who currently works as a lecturer and researcher at the Department of Linguistics in Tübingen. My current research focuses on the development of novel approaches to the interpretation of non-standard language (as part of Prof. Detmar Meurers' ICALL research group), and on developing new interactive tools for historical linguistics as a continuation of my PhD work in Prof. Gerhard Jäger's group. As part of the latter, I am also the main contributor and coordinator for the NorthEuraLex database.

Until recently, I was a doctoral student in the EVOLAEMP project, under the supervision of Prof. Gerhard Jäger. For my PhD project, I worked on the application of causal inference methods to problems of historical linguistics.

Before the PhD, I completed M.A. and B.A. degrees in the International Studies in Computational Linguistics program at the University of Tübingen. In parallel, I acquired a Diplom (M.S.) degree in computer science at the Department of Computer Science in Tübingen, with a minor in mathematics.

Current Research Interests:

Computational Historical Linguistics: My continuing focus is on applications of quantitative and statistical methods to answering research questions in historical linguistics. The main goal is to improve and advance these methods by incorporating linguistic domain knowledge, instead of directly and uncritically applying off-the-shelf tools e.g. from bioinformatics.

Interpreting Non-Standard Language: My second focus is on the development of new approaches to natural language understanding in situations where higher levels of linguistic analysis (like semantics) are needed to guide the interpretation on lower levels of analysis (like morphology), which is the case whenever non-standard usage is involved. My main example of such a situation is the automated interpretation and analysis of German learner answers.

Older Research Interests:

Causal Inference: Recent mathematical models allow to infer causal knowledge from non-experimental data on the basis of conditional independencies between observed variables. I have explored the use of such methods for detecting causal patterns in linguistic data. Within the EVOLAEMP project, the primary focus of this work was on using causal inference to infer what I call lexical flow networks from automatically inferred cognate sets.

Computational Semantics: My main area of interest within computational linguistics, where I have been involved in developing specialized reasoning tools which better meet the demands of linguistic applications. This especially concerns the area of model generation, where I am developing specialized heuristics for more rapid construction of linguistically adequate models.

Automated Reasoning: Beyond my interest in reasoning tools for computational semantics, I have also been doing work on the extraction of Minimal Unsatisfiable Subsets from unsatisfiable SAT problems. This has applications in many areas where minimal explanations for observations are needed.

Grammar Engineering: Systems for implementing symbolic grammars in complex grammar formalisms are very helpful tools for validating linguistic theories. I have been involved in developing and extending environments for the HPSG and TAG formalisms with the goal of making their behavior more transparent.


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