Jari Björne


2018

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Biomedical Event Extraction Using Convolutional Neural Networks and Dependency Parsing
Jari Björne | Tapio Salakoski
Proceedings of the BioNLP 2018 workshop

Event and relation extraction are central tasks in biomedical text mining. Where relation extraction concerns the detection of semantic connections between pairs of entities, event extraction expands this concept with the addition of trigger words, multiple arguments and nested events, in order to more accurately model the diversity of natural language. In this work we develop a convolutional neural network that can be used for both event and relation extraction. We use a linear representation of the input text, where information is encoded with various vector space embeddings. Most notably, we encode the parse graph into this linear space using dependency path embeddings. We integrate our neural network into the open source Turku Event Extraction System (TEES) framework. Using this system, our machine learning model can be easily applied to a large set of corpora from e.g. the BioNLP, DDI Extraction and BioCreative shared tasks. We evaluate our system on 12 different event, relation and NER corpora, showing good generalizability to many tasks and achieving improved performance on several corpora.

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The 2018 Shared Task on Extrinsic Parser Evaluation: On the Downstream Utility of English Universal Dependency Parsers
Murhaf Fares | Stephan Oepen | Lilja Øvrelid | Jari Björne | Richard Johansson
Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies

We summarize empirical results and tentative conclusions from the Second Extrinsic Parser Evaluation Initiative (EPE 2018). We review the basic task setup, downstream applications involved, and end-to-end results for seventeen participating teams. Based on in-depth quantitative and qualitative analysis, we correlate intrinsic evaluation results at different layers of morph-syntactic analysis with observed downstream behavior.

2017

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End-to-End System for Bacteria Habitat Extraction
Farrokh Mehryary | Kai Hakala | Suwisa Kaewphan | Jari Björne | Tapio Salakoski | Filip Ginter
BioNLP 2017

We introduce an end-to-end system capable of named-entity detection, normalization and relation extraction for extracting information about bacteria and their habitats from biomedical literature. Our system is based on deep learning, CRF classifiers and vector space models. We train and evaluate the system on the BioNLP 2016 Shared Task Bacteria Biotope data. The official evaluation shows that the joint performance of our entity detection and relation extraction models outperforms the winning team of the Shared Task by 19pp on F1-score, establishing a new top score for the task. We also achieve state-of-the-art results in the normalization task. Our system is open source and freely available at https://github.com/TurkuNLP/BHE.

2016

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UTU at SemEval-2016 Task 10: Binary Classification for Expression Detection (BCED)
Jari Björne | Tapio Salakoski
Proceedings of the 10th International Workshop on Semantic Evaluation (SemEval-2016)

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Deep Learning with Minimal Training Data: TurkuNLP Entry in the BioNLP Shared Task 2016
Farrokh Mehryary | Jari Björne | Sampo Pyysalo | Tapio Salakoski | Filip Ginter
Proceedings of the 4th BioNLP Shared Task Workshop

2013

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UTurku: Drug Named Entity Recognition and Drug-Drug Interaction Extraction Using SVM Classification and Domain Knowledge
Jari Björne | Suwisa Kaewphan | Tapio Salakoski
Second Joint Conference on Lexical and Computational Semantics (*SEM), Volume 2: Proceedings of the Seventh International Workshop on Semantic Evaluation (SemEval 2013)

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TEES 2.1: Automated Annotation Scheme Learning in the BioNLP 2013 Shared Task
Jari Björne | Tapio Salakoski
Proceedings of the BioNLP Shared Task 2013 Workshop

2012

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PubMed-Scale Event Extraction for Post-Translational Modifications, Epigenetics and Protein Structural Relations
Jari Björne | Sofie Van Landeghem | Sampo Pyysalo | Tomoko Ohta | Filip Ginter | Yves Van de Peer | Sophia Ananiadou | Tapio Salakoski
BioNLP: Proceedings of the 2012 Workshop on Biomedical Natural Language Processing

2011

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Generalizing Biomedical Event Extraction
Jari Björne | Tapio Salakoski
Proceedings of BioNLP Shared Task 2011 Workshop

2010

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Scaling up Biomedical Event Extraction to the Entire PubMed
Jari Björne | Filip Ginter | Sampo Pyysalo | Jun’ichi Tsujii | Tapio Salakoski
Proceedings of the 2010 Workshop on Biomedical Natural Language Processing

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Reconstruction of Semantic Relationships from Their Projections in Biomolecular Domain
Juho Heimonen | Jari Björne | Tapio Salakoski
Proceedings of the 2010 Workshop on Biomedical Natural Language Processing

2009

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Extracting Complex Biological Events with Rich Graph-Based Feature Sets
Jari Björne | Juho Heimonen | Filip Ginter | Antti Airola | Tapio Pahikkala | Tapio Salakoski
Proceedings of the BioNLP 2009 Workshop Companion Volume for Shared Task

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Learning to Extract Biological Event and Relation Graphs
Jari Björne | Filip Ginter | Juho Heimonen | Sampo Pyysalo | Tapio Salakoski
Proceedings of the 17th Nordic Conference of Computational Linguistics (NODALIDA 2009)

2008

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A Graph Kernel for Protein-Protein Interaction Extraction
Antti Airola | Sampo Pyysalo | Jari Björne | Tapio Pahikkala | Filip Ginter | Tapio Salakoski
Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing