Update March 2017:
The update contains
- an improved version of the coreference resolver Download link
- a conversion tool for linux that converts plain texts into the required input format CoNLL-12 (using the same tools that were used during training) Link to GitHub
The German coreference system described in the LREC 2016 paper  and in the ACL paper  can be downloaded below.
The download includes
- a manual on how to run the resolver
- default feature lists as well as an overview of the features that one can play around with
- example documents in CoNLL-12 format, including pos tags, parse bits, lemmata, morphological information and named entities (optional)
Note: the resolver is among other things based on the extraction of NPs from the parse bits. Some parsers for German do not annotate NPs inside PPs (=they are flat), so you need to insert them before running the tool.
Here's a manual on how to run the resolver
- new model trained on the completeTüBa-D/Z version 10 data using regular processing with the improved version of the coreference resolver available here
Older models: (trained with LREC version)
- trained on the complete TüBa-D/Z version 10 data, gold processing available here
- trained on the complete TüBa-D/Z version 10 data, regular processing available here
- trained on the complete TüBa-D/Z, version 9, regular processing is available here
CoNLL scores as published in :
- 65.76 (no singletons) on the TüBa-D/Z test set version 10, using gold annotations
- 48.54 (including singletons) on the TüBa-D/Z test set version 10, using regular annotations
The older performance (as reported in the paper , using real preprocessing/predicted annotations only and no gold mention boundary (GB) information) is as follows:
- 51.61 (no singletons) on the TüBa-D/Z test set version 9
- 60.35 (including singletons) and 48.61 (without) on the TüBa-D/Z test set version 8 (=SemEval dataset) (in CoNLL score)
This version of the system is licensed under the GNU General Public License. For questions contact Anders Björkelund (firstname.lastname@example.org).
 Ina Rösiger and Jonas Kuhn
IMS HotCoref De: A data-driven co-reference resolver for German
Proceedings of LREC 2016, Portorož, Slovenia 2016.
 Ina Rösiger and Arndt Riester
Using prosodic annotations to improve coreference resolution of spoken text.
Proceedings of ACL-IJCNLP 2015, Beijing, China.
- Download the German co-reference system and the manual how to run the resolver
- Download the older German co-reference system as published in the LREC 2016 paper  amd the manual how to run the resolver
- Download the older German prototype as published in ACL 2015  and the manual how to run the resolver