Éva Mújdricza-Maydt


2017

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Assessing SRL Frameworks with Automatic Training Data Expansion
Silvana Hartmann | Éva Mújdricza-Maydt | Ilia Kuznetsov | Iryna Gurevych | Anette Frank
Proceedings of the 11th Linguistic Annotation Workshop

We present the first experiment-based study that explicitly contrasts the three major semantic role labeling frameworks. As a prerequisite, we create a dataset labeled with parallel FrameNet-, PropBank-, and VerbNet-style labels for German. We train a state-of-the-art SRL tool for German for the different annotation styles and provide a comparative analysis across frameworks. We further explore the behavior of the frameworks with automatic training data generation. VerbNet provides larger semantic expressivity than PropBank, and we find that its generalization capacity approaches PropBank in SRL training, but it benefits less from training data expansion than the sparse-data affected FrameNet.

2016

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A Web-based Tool for the Integrated Annotation of Semantic and Syntactic Structures
Richard Eckart de Castilho | Éva Mújdricza-Maydt | Seid Muhie Yimam | Silvana Hartmann | Iryna Gurevych | Anette Frank | Chris Biemann
Proceedings of the Workshop on Language Technology Resources and Tools for Digital Humanities (LT4DH)

We introduce the third major release of WebAnno, a generic web-based annotation tool for distributed teams. New features in this release focus on semantic annotation tasks (e.g. semantic role labelling or event annotation) and allow the tight integration of semantic annotations with syntactic annotations. In particular, we introduce the concept of slot features, a novel constraint mechanism that allows modelling the interaction between semantic and syntactic annotations, as well as a new annotation user interface. The new features were developed and used in an annotation project for semantic roles on German texts. The paper briefly introduces this project and reports on experiences performing annotations with the new tool. On a comparative evaluation, our tool reaches significant speedups over WebAnno 2 for a semantic annotation task.

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Combining Semantic Annotation of Word Sense & Semantic Roles: A Novel Annotation Scheme for VerbNet Roles on German Language Data
Éva Mújdricza-Maydt | Silvana Hartmann | Iryna Gurevych | Anette Frank
Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)

We present a VerbNet-based annotation scheme for semantic roles that we explore in an annotation study on German language data that combines word sense and semantic role annotation. We reannotate a substantial portion of the SALSA corpus with GermaNet senses and a revised scheme of VerbNet roles. We provide a detailed evaluation of the interaction between sense and role annotation. The resulting corpus will allow us to compare VerbNet role annotation for German to FrameNet and PropBank annotation by mapping to existing role annotations on the SALSA corpus. We publish the annotated corpus and detailed guidelines for the new role annotation scheme.

2012

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A Multigraph Model for Coreference Resolution
Sebastian Martschat | Jie Cai | Samuel Broscheit | Éva Mújdricza-Maydt | Michael Strube
Joint Conference on EMNLP and CoNLL - Shared Task

2011

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Unrestricted Coreference Resolution via Global Hypergraph Partitioning
Jie Cai | Éva Mújdricza-Maydt | Michael Strube
Proceedings of the Fifteenth Conference on Computational Natural Language Learning: Shared Task