M
Michael Schmitz
Researcher at Voith
Publications - 16
Citations - 2203
Michael Schmitz is an academic researcher from Voith. The author has contributed to research in topics: Concurrent ML & Perforation (oil well). The author has an hindex of 5, co-authored 15 publications receiving 1825 citations. Previous affiliations of Michael Schmitz include University of Washington.
Papers
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Proceedings Article
Open Language Learning for Information Extraction
TL;DR: Ollie as mentioned in this paper improves ReVerb by extracting relations mediated by nouns, adjectives, and more, and adds context information from the sentence in the extractions to increase precision.
Posted Content
AllenNLP: A Deep Semantic Natural Language Processing Platform
Matt Gardner,Joel Grus,Mark Neumann,Oyvind Tafjord,Pradeep Dasigi,Nelson F. Liu,Matthew E. Peters,Michael Schmitz,Luke Zettlemoyer +8 more
TL;DR: AllenNLP is designed to support researchers who want to build novel language understanding models quickly and easily and provides a flexible data API that handles intelligent batching and padding, and a modular and extensible experiment framework that makes doing good science easy.
Proceedings ArticleDOI
AllenNLP: A Deep Semantic Natural Language Processing Platform
Matt Gardner,Joel Grus,Mark Neumann,Oyvind Tafjord,Pradeep Dasigi,Nelson F. Liu,Matthew E. Peters,Michael Schmitz,Luke Zettlemoyer +8 more
TL;DR: AllenNLP as mentioned in this paper is a library for applying deep learning methods to NLP research that addresses these issues with easy-to-use command-line tools, declarative configuration-driven experiments, and modular NLP abstractions.
Patent
Use of lexical translations for facilitating searches
TL;DR: The authors used triangulation to identify pairs of common wordsense translations between a first, second, and third language between a plurality of different languages, which can then be used for searches of a data collection in different languages.
Posted Content
From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project
Peter Clark,Oren Etzioni,Daniel Khashabi,Tushar Khot,Bhavana Dalvi Mishra,Kyle Richardson,Ashish Sabharwal,Carissa Schoenick,Oyvind Tafjord,Niket Tandon,Sumithra Bhakthavatsalam,Dirk Groeneveld,Michal Guerquin,Michael Schmitz +13 more
TL;DR: Success is reported on the Grade 8 New York Regents Science Exam, where for the first time a system scores more than 90 percent on the exam’s nondiagram, multiple choice (NDMC) questions, demonstrating that modern natural language processing methods can result in mastery on this task.