Silvana Hartmann


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An Integrated Representation of Linguistic and Social Functions of Code-Switching
Silvana Hartmann | Monojit Choudhury | Kalika Bali
Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)


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Out-of-domain FrameNet Semantic Role Labeling
Silvana Hartmann | Ilia Kuznetsov | Teresa Martin | Iryna Gurevych
Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers

Domain dependence of NLP systems is one of the major obstacles to their application in large-scale text analysis, also restricting the applicability of FrameNet semantic role labeling (SRL) systems. Yet, current FrameNet SRL systems are still only evaluated on a single in-domain test set. For the first time, we study the domain dependence of FrameNet SRL on a wide range of benchmark sets. We create a novel test set for FrameNet SRL based on user-generated web text and find that the major bottleneck for out-of-domain FrameNet SRL is the frame identification step. To address this problem, we develop a simple, yet efficient system based on distributed word representations. Our system closely approaches the state-of-the-art in-domain while outperforming the best available frame identification system out-of-domain. We publish our system and test data for research purposes.

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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.


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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.

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Generating Training Data for Semantic Role Labeling based on Label Transfer from Linked Lexical Resources
Silvana Hartmann | Judith Eckle-Kohler | Iryna Gurevych
Transactions of the Association for Computational Linguistics, Volume 4

We present a new approach for generating role-labeled training data using Linked Lexical Resources, i.e., integrated lexical resources that combine several resources (e.g., Word-Net, FrameNet, Wiktionary) by linking them on the sense or on the role level. Unlike resource-based supervision in relation extraction, we focus on complex linguistic annotations, more specifically FrameNet senses and roles. The automatically labeled training data ( are evaluated on four corpora from different domains for the tasks of word sense disambiguation and semantic role classification. Results show that classifiers trained on our generated data equal those resulting from a standard supervised setting.

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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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FrameNet on the Way to Babel: Creating a Bilingual FrameNet Using Wiktionary as Interlingual Connection
Silvana Hartmann | Iryna Gurevych
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)


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UBY - A Large-Scale Unified Lexical-Semantic Resource Based on LMF
Iryna Gurevych | Judith Eckle-Kohler | Silvana Hartmann | Michael Matuschek | Christian M. Meyer | Christian Wirth
Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics

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UBY-LMF – A Uniform Model for Standardizing Heterogeneous Lexical-Semantic Resources in ISO-LMF
Judith Eckle-Kohler | Iryna Gurevych | Silvana Hartmann | Michael Matuschek | Christian M. Meyer
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

We present UBY-LMF, an LMF-based model for large-scale, heterogeneous multilingual lexical-semantic resources (LSRs). UBY-LMF allows the standardization of LSRs down to a fine-grained level of lexical information by employing a large number of Data Categories from ISOCat. We evaluate UBY-LMF by converting nine LSRs in two languages to the corresponding format: the English WordNet, Wiktionary, Wikipedia, OmegaWiki, FrameNet and VerbNet and the German Wikipedia, Wiktionary and GermaNet. The resulting LSR, UBY (Gurevych et al., 2012), holds interoperable versions of all nine resources which can be queried by an easy to use public Java API. UBY-LMF covers a wide range of information types from expert-constructed and collaboratively constructed resources for English and German, also including links between different resources at the word sense level. It is designed to accommodate further resources and languages as well as automatically mined lexical-semantic knowledge.

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The Open Linguistics Working Group
Christian Chiarcos | Sebastian Hellmann | Sebastian Nordhoff | Steven Moran | Richard Littauer | Judith Eckle-Kohler | Iryna Gurevych | Silvana Hartmann | Michael Matuschek | Christian M. Meyer
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper describes the Open Linguistics Working Group (OWLG) of the Open Knowledge Foundation (OKFN). The OWLG is an initiative concerned with linguistic data by scholars from diverse fields, including linguistics, NLP, and information science. The primary goal of the working group is to promote the idea of open linguistic resources, to develop means for their representation and to encourage the exchange of ideas across different disciplines. This paper summarizes the progress of the working group, goals that have been identified, problems that we are going to address, and recent activities and ongoing developments. Here, we put particular emphasis on the development of a Linked Open Data (sub-)cloud of linguistic resources that is currently being pursued by several OWLG members.


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Large-scale Computation of Distributional Similarities for Queries
Enrique Alfonseca | Keith Hall | Silvana Hartmann
Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers