Alex Judea


2017

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Event Argument Identification on Dependency Graphs with Bidirectional LSTMs
Alex Judea | Michael Strube
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

In this paper we investigate the performance of event argument identification. We show that the performance is tied to syntactic complexity. Based on this finding, we propose a novel and effective system for event argument identification. Recurrent Neural Networks learn to produce meaningful representations of long and short dependency paths. Convolutional Neural Networks learn to decompose the lexical context of argument candidates. They are combined into a simple system which outperforms a feature-based, state-of-the-art event argument identifier without any manual feature engineering.

2016

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Incremental Global Event Extraction
Alex Judea | Michael Strube
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers

Event extraction is a difficult information extraction task. Li et al. (2014) explore the benefits of modeling event extraction and two related tasks, entity mention and relation extraction, jointly. This joint system achieves state-of-the-art performance in all tasks. However, as a system operating only at the sentence level, it misses valuable information from other parts of the document. In this paper, we present an incremental easy-first approach to make the global context of the entire document available to the intra-sentential, state-of-the-art event extractor. We show that our method robustly increases performance on two datasets, namely ACE 2005 and TAC 2015.

2015

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Event Extraction as Frame-Semantic Parsing
Alex Judea | Michael Strube
Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

2014

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Unsupervised Training Set Generation for Automatic Acquisition of Technical Terminology in Patents
Alex Judea | Hinrich Schütze | Soeren Bruegmann
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers

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Dependency parsing with latent refinements of part-of-speech tags
Thomas Mueller | Richard Farkas | Alex Judea | Helmut Schmid | Hinrich Schuetze
Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)

2012

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Concept-based Selectional Preferences and Distributional Representations from Wikipedia Articles
Alex Judea | Vivi Nastase | Michael Strube
Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC'12)

This paper describes the derivation of distributional semantic representations for open class words relative to a concept inventory, and of concepts relative to open class words through grammatical relations extracted from Wikipedia articles. The concept inventory comes from WikiNet, a large-scale concept network derived from Wikipedia. The distinctive feature of these representations are their relation to a concept network, through which we can compute selectional preferences of open-class words relative to general concepts. The resource thus derived provides a meaning representation that complements the relational representation captured in the concept network. It covers English open-class words, but the concept base is language independent. The resource can be extended to other languages, with the use of language specific dependency parsers. Good results in metonymy resolution show the resource's potential use for NLP applications.

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Local and Global Context for Supervised and Unsupervised Metonymy Resolution
Vivi Nastase | Alex Judea | Katja Markert | Michael Strube
Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

2011

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WikiNetTK – A Tool Kit for EmbeddingWorld Knowledge in NLP Applications
Alex Judea | Vivi Nastase | Michael Strube
Proceedings of the IJCNLP 2011 System Demonstrations