Open AccessProceedings Article
Overview of BioNLP Shared Task 2013
Claire Nédellec,Robert Bossy,Jin-Dong Kim,Jung-Jae Kim,Tomoko Ohta,Sampo Pyysalo,Pierre Zweigenbaum +6 more
- pp 1-7
TLDR
The BioNLP Shared Task 2013 shows advances in the state of the art and demonstrates that extraction methods can be successfully generalized in various aspects.Citations
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FoodBase corpus: a new resource of annotated food entities.
TL;DR: A new annotated corpus of food entities, named FoodBase, was developed using recipes extracted from Allrecipes, which is currently the largest food-focused social network and is necessary for developing corpus-based NER models for food science, as a new benchmark dataset for machine learning tasks such as multi-class classification, multi-label classification and hierarchical multi- label classification.
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BELMiner: adapting a rule-based relation extraction system to extract biological expression language statements from bio-medical literature evidence sentences
TL;DR: This work tested the ability of a rule-based semantic parser to extract Biological Expression Language statements from evidence sentences culled out of biomedical literature as part of BioCreative V Track4 challenge and found a marked improvement by over 20% in the overall performance of the BELMiner’s capability to extract BEL statement on the test set.
Proceedings ArticleDOI
Using word embedding for bio-event extraction
TL;DR: By using bag-ofwords (BOW) features as the baseline, the result has been improved by the introduction of word-embedding features, and is comparable to the state-of-the-art solution.
Proceedings ArticleDOI
VERSE: Event and Relation Extraction in the BioNLP 2016 Shared Task
Jake Lever,Steven J.M. Jones +1 more
TL;DR: The Vancouver Event and Relation System for Extraction (VERSE)1 is presented as a competing system for three subtasks of the BioNLP Shared Task 2016.
Journal ArticleDOI
A semi-supervised learning framework for biomedical event extraction based on hidden topics
Deyu Zhou,Dayou Zhong +1 more
TL;DR: By incorporating un-annotated data, the proposed framework indeed improves the performance of the state-of-the-art event extraction system and the similarity between sentences might be precisely described by hidden topics and structures of the sentences.
References
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Proceedings ArticleDOI
Coarse-to-Fine n-Best Parsing and MaxEnt Discriminative Reranking
Eugene Charniak,Mark Johnson +1 more
TL;DR: This paper describes a simple yet novel method for constructing sets of 50- best parses based on a coarse-to-fine generative parser that generates 50-best lists that are of substantially higher quality than previously obtainable.
Proceedings ArticleDOI
Overview of BioNLP'09 Shared Task on Event Extraction
TL;DR: The design and implementation of the BioNLP'09 Shared Task is presented, indicating that state-of-the-art performance is approaching a practically applicable level and revealing some remaining challenges.
Performance measures for information extraction
TL;DR: An error measure is defined, the slot error rate, which combines the different types of error directly, without having to resort to precision and recall as preliminary measures.
Book ChapterDOI
PANTHER Pathway: An Ontology-Based Pathway Database Coupled with Data Analysis Tools
Huaiyu Mi,Paul Thomas +1 more
TL;DR: This chapter first discusses how biological knowledge is represented, particularly the importance of ontologies or standards in systems biology research, and uses PANTHER Pathway as an example to illustrate how ontologies and standards play a role in data modeling, data entry, and data display.
Journal ArticleDOI
Evaluating temporal relations in clinical text: 2012 i2b2 Challenge.
TL;DR: A corpus of discharge summaries annotated with temporal information was provided to be used for the development and evaluation of temporal reasoning systems, and the best systems overwhelmingly adopted a rule based approach for value normalization.