Sophia Katrenko


2017

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Tagging Funding Agencies and Grants in Scientific Articles using Sequential Learning Models
Subhradeep Kayal | Zubair Afzal | George Tsatsaronis | Sophia Katrenko | Pascal Coupet | Marius Doornenbal | Michelle Gregory
BioNLP 2017

In this paper we present a solution for tagging funding bodies and grants in scientific articles using a combination of trained sequential learning models, namely conditional random fields (CRF), hidden markov models (HMM) and maximum entropy models (MaxEnt), on a benchmark set created in-house. We apply the trained models to address the BioASQ challenge 5c, which is a newly introduced task that aims to solve the problem of funding information extraction from scientific articles. Results in the dry-run data set of BioASQ task 5c show that the suggested approach can achieve a micro-recall of more than 85% in tagging both funding bodies and grants.

2014

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Towards a Semantic Model for Textual Entailment Annotation
Assaf Toledo | Stavroula Alexandropoulou | Sophie Chesney | Sophia Katrenko | Heid Klockmann | Pepjin Kokke | Benno Kruit | Yoad Winter
Linguistic Issues in Language Technology, Volume 9, 2014 - Perspectives on Semantic Representations for Textual Inference

We introduce a new formal semantic model for annotating textual entailments that describes restrictive, intersective, and appositive modification. The model contains a formally defined interpreted lexicon, which specifies the inventory of symbols and the supported semantic operators, and an informally defined annotation scheme that instructs annotators in which way to bind words and constructions from a given pair of premise and hypothesis to the interpreted lexicon. We explore the applicability of the proposed model to the Recognizing Textual Entailment (RTE) 1–4 corpora and describe a first-stage annotation scheme on which we based the manual annotation work. The constructions we annotated were found to occur in 80.65% of the entailments in RTE 1–4 and were annotated with cross-annotator agreement of 68% on average. The annotated parts of the RTE corpora are publicly available for further research.

2013

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Semantic Annotation of Textual Entailment
Assaf Toledo | Stavroula Alexandropoulou | Sophia Katrenko | Heidi Klockmann | Pepijn Kokke | Yoad Winter
Proceedings of the 10th International Conference on Computational Semantics (IWCS 2013) – Long Papers

2012

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“Could you make me a favour and do coffee, please?”: Implications for Automatic Error Correction in English and Dutch
Sophia Katrenko
*SEM 2012: The First Joint Conference on Lexical and Computational Semantics – Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation (SemEval 2012)

2008

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Semantic Types of Some Generic Relation Arguments: Detection and Evaluation
Sophia Katrenko | Pieter Adriaans
Proceedings of ACL-08: HLT, Short Papers

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A Local Alignment Kernel in the Context of NLP
Sophia Katrenko | Pieter Adriaans
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)

2007

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Named Entity Recognition for Ukrainian: A Resource-Light Approach
Sophia Katrenko | Pieter Adriaans
Proceedings of the Workshop on Balto-Slavonic Natural Language Processing

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UVAVU: WordNet Similarity and Lexical Patterns for Semantic Relation Classification
Willem Robert van Hage | Sophia Katrenko
Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007)