# Britta D. Zeller
**Britta D. Zeller** (also published as Britta Zeller) is a computational linguist who worked in natural language processing at the Institut für Computerlinguistik (Institute of Computational Linguistics) of Heidelberg University.[1](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml) She is known for work on derivational morphology and distributional semantics, above all the DErivBase lexicon of German derivational word families and the technique of derivational smoothing (using word-formation info to improve meaning models), both published at the 2013 annual meeting of the [Association for Computational Linguistics](https://www.edgepedia.org/association-for-computational-linguistics) (ACL).[2](https://aclanthology.org/P13-1118/) • [3](https://aclanthology.org/P13-2128/) After submitting her doctoral thesis in May 2015 she moved to industry, joining the company Molecular Health.[1](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml)
| Key fact | Detail |
|---|---|
| Field | Computational linguistics / natural language processing |
| Doctoral training | Heidelberg University, Institut für Computerlinguistik; thesis submitted May 2015, supervised by Sebastian Padó[4](https://doi.org/10.11588/heidok.00020539) • [1](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml) |
| Master's thesis | *Corpus-based Acquisition and Analysis of Support Verb Constructions*, University of Heidelberg, 2011[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml) |
| Signature work | *DErivBase: Inducing and Evaluating a Derivational Morphology Resource for German* (ACL 2013) and *Derivational Smoothing for Syntactic Distributional Semantics* (ACL 2013)[2](https://aclanthology.org/P13-1118/) • [3](https://aclanthology.org/P13-2128/) |
| DErivBase scale | Over 280,000 German lemmas in more than 17,000 non-singleton derivational clusters; up to 93% precision and 71% recall[2](https://aclanthology.org/P13-1118/) |
| Career after academia | Molecular Health, from after May 2015[1](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml) |
## Career and training
Zeller completed her master's degree at the University of Heidelberg in 2011 with a thesis titled *Corpus-based Acquisition and Analysis of Support Verb Constructions*.[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml) That work continued in a 2012 Springer book chapter, *Corpus-based acquisition of support verb constructions for portuguese*, in *Lecture Notes in Computer Science* volume 7243, pages 73–84; she also appears among the co-authors of a 2011 Springer collection chapter on adapting NLP tools and frame-semantic resources for the semantic analysis of ritual descriptions.[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml)
According to her thesis *Induction, Semantic Validation and Evaluation of a Derivational Morphology Lexicon for German*,[4](https://doi.org/10.11588/heidok.00020539) she carried out her doctoral research at Heidelberg's Institut für Computerlinguistik under the supervision of [Sebastian Padó](https://www.edgepedia.org/sebastian-pado). Her own bibliography dates the thesis 2015, and she records handing it in in May 2015; the [Heidelberg](https://www.edgepedia.org/heidelberg) university repository (heiDOK) record for the same thesis carries the DOI 10.11588/heidok.00020539 and is dated 2016, so the two records differ on the publication year.[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml) • [1](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml) • [4](https://doi.org/10.11588/heidok.00020539) In the thesis she credits her supervisor with support throughout the work and thanks a collaborator from the [University of Zagreb](https://www.edgepedia.org/university-of-zagreb) for bringing the thesis topic from Zagreb to Heidelberg.[4](https://doi.org/10.11588/heidok.00020539) She states her three main contributions as a pre-study of German derivation, the implementation of the derivation rules, and the analysis of the rules, and the resulting lexicon, including error analysis.[4](https://doi.org/10.11588/heidok.00020539) After submitting the thesis she went to work for Molecular Health, and her Heidelberg website was closed thereafter.[1](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml)
## Representative work
DErivBase, presented at ACL 2013 in Sofia, Bulgaria (pages 1201–1211 of the long papers volume), describes a rule-based framework for inducing derivational families, clusters of lemmas in derivational relationships, and its application to build a high-coverage German resource mapping over 280,000 lemmas into more than 17,000 non-singleton clusters.[2](https://aclanthology.org/P13-1118/) • [5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml) The approach achieves up to 93% precision and 71% recall, with the high precision attributed to rules based on information from grammar books.[2](https://aclanthology.org/P13-1118/) The resource is freely available, and the authors state that the induction approach is not restricted to German.[2](https://aclanthology.org/P13-1118/)
According to the ACL Anthology, the companion short paper at the same conference, *Derivational Smoothing for Syntactic Distributional Semantics* (ACL 2013, Volume 2: Short Papers, Sofia, pp. 731–735), developed the use of derivational information to improve syntactic distributional semantic models.[3](https://aclanthology.org/P13-2128/)
## How DErivBase was built and validated
The lexicon is induced by combining rule-based and data-driven methods: linguistic derivation rules define the derivational processes, and lemmas extracted from a German corpus are fed into the rules to derive new lemmas.[4](https://doi.org/10.11588/heidok.00020539) The rule-based framework the thesis builds on had existed previously.[4](https://doi.org/10.11588/heidok.00020539)
A second version of the lexicon adds semantic validation: derivational families are subdivided into semantically coherent clusters using a supervised binary classifier built from structural features of the derivation rules and from distributional features measuring the semantic relatedness of lemmas.[4](https://doi.org/10.11588/heidok.00020539) This validation work was disseminated in the COLING 2014 paper *Towards Semantic Validation of a Derivational Lexicon*, published in Dublin, Ireland, pp. 1728–1739.[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml) The thesis evaluates the lexicon versions on three extrinsic semantic tasks, including incorporating DErivBase into distributional semantic models via derivational smoothing and psycholinguistic experiments published in 2015.[4](https://doi.org/10.11588/heidok.00020539) A related earlier output was the IWCS 2013 paper *A Search Task Dataset for German Textual Entailment*, presented in Potsdam, pp. 288–299.[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml) A 2015 conference abstract, *Morphological priming in german: The word is not enough (or is it?)*, was accepted at the NetWords Conference in Pisa, Italy.[5](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml)
The distributed resource reflects the two versions. The [Stuttgart](https://www.edgepedia.org/stuttgart) distribution page describes DErivBase as a large-coverage derivational lexicon for German consisting of derivational families, and notes that since version 2.0 the families are automatically split into semantically consistent clusters.[6](https://www.ims.uni-stuttgart.de/en/research/resources/lexica/derivbase/) Version 2.0 covers 280,336 lemmas, of which 65,420 are grouped into 20,371 non-singleton families and 214,916 remain singletons; it was extracted from SDeWAC, a large German web corpus, with HOFM, a rule-based framework written in Haskell.[6](https://www.ims.uni-stuttgart.de/en/research/resources/lexica/derivbase/) The 2013 paper's figures (over 280k lemmas, more than 17k non-singleton clusters) describe the original release, so the two sets of numbers correspond to different versions rather than disagreeing on one quantity.[2](https://aclanthology.org/P13-1118/) • [6](https://www.ims.uni-stuttgart.de/en/research/resources/lexica/derivbase/)
The authors frame their work against a gap they state themselves: derivational models were, in their words, still an under-researched area in computational morphology, and even for German, a rather resource-rich language, there was a lack of large-coverage derivational knowledge.[2](https://aclanthology.org/P13-1118/) DErivBase was built to supply that missing large-coverage resource.[2](https://aclanthology.org/P13-1118/)
## References
1. [Britta D. Zeller, M.A., Institut für Computerlinguistik, Heidelberg University](https://www.cl.uni-heidelberg.de/~zeller/index_en.mhtml)
2. [DErivBase: Inducing and Evaluating a Derivational Morphology Resource for German, ACL Anthology](https://aclanthology.org/P13-1118/)
3. [Derivational Smoothing for Syntactic Distributional Semantics, ACL Anthology](https://aclanthology.org/P13-2128/)
4. [Induction, Semantic Validation and Evaluation of a Derivational Morphology Lexicon for German (PhD thesis, heiDOK)](https://doi.org/10.11588/heidok.00020539)
5. [publics.bib, Zeller's bibliography file, Heidelberg ICL](https://www.cl.uni-heidelberg.de/~zeller/publics_bib.mhtml)
6. [DErivBase and DErivCELEX, Institute for Natural Language Processing, University of Stuttgart](https://www.ims.uni-stuttgart.de/en/research/resources/lexica/derivbase/)
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*Initially written Sep 21, 2026 · Reviewed: Sep 25, 2026 · Edited: Sep 25, 2026 · Last review: Sep 25, 2026*
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