Konstantina Garoufi


2014

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Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics
Shuly Wintner | Desmond Elliott | Konstantina Garoufi | Douwe Kiela | Ivan Vulić
Proceedings of the Student Research Workshop at the 14th Conference of the European Chapter of the Association for Computational Linguistics

2012

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Enhancing Referential Success by Tracking Hearer Gaze
Alexander Koller | Konstantina Garoufi | Maria Staudte | Matthew Crocker
Proceedings of the 13th Annual Meeting of the Special Interest Group on Discourse and Dialogue

2011

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Combining symbolic and corpus-based approaches for the generation of successful referring expressions
Konstantina Garoufi | Alexander Koller
Proceedings of the 13th European Workshop on Natural Language Generation

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Report on the Second Second Challenge on Generating Instructions in Virtual Environments (GIVE-2.5)
Kristina Striegnitz | Alexandre Denis | Andrew Gargett | Konstantina Garoufi | Alexander Koller | Mariët Theune
Proceedings of the 13th European Workshop on Natural Language Generation

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The Potsdam NLG systems at the GIVE-2.5 Challenge
Konstantina Garoufi | Alexander Koller
Proceedings of the 13th European Workshop on Natural Language Generation

2010

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Automated Planning for Situated Natural Language Generation
Konstantina Garoufi | Alexander Koller
Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics

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The GIVE-2 Corpus of Giving Instructions in Virtual Environments
Andrew Gargett | Konstantina Garoufi | Alexander Koller | Kristina Striegnitz
Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10)

We present the GIVE-2 Corpus, a new corpus of human instruction giving. The corpus was collected by asking one person in each pair of subjects to guide the other person towards completing a task in a virtual 3D environment with typed instructions. This is the same setting as that of the recent GIVE Challenge, and thus the corpus can serve as a source of data and as a point of comparison for NLG systems that participate in the GIVE Challenge. The instruction-giving data we collect is multilingual (45 German and 63 English dialogues), and can easily be extended to further languages by using our software, which we have made available. We analyze the corpus to study the effects of learning by repeated participation in the task and the effects of the participants' spatial navigation abilities. Finally, we present a novel annotation scheme for situated referring expressions and compare the referring expressions in the German and English data.