Results 61 to 70 of about 316,892 (282)
What Do Large Language Models Know About Materials?
Advanced Engineering Materials, EarlyView.If large language models (LLMs) are to be used inside the material discovery and engineering process, they must be benchmarked for the accurateness of intrinsic material knowledge. The current work introduces 1) a reasoning process through the processing–structure–property–performance chain and 2) a tool for benchmarking knowledge of LLMs concerning ...
Adrian Ehrenhofer +2 more
wiley +1 more source
CRFVoter: gene and protein related object recognition using a conglomerate of CRF-based tools
Journal of Cheminformatics, 2019 Background Gene and protein related objects are an important class of entities in biomedical research, whose identification and extraction from scientific articles is attracting increasing interest.
Wahed Hemati, Alexander Mehler
doaj +1 more source
Advanced Engineering Materials, EarlyView.This article presents the NFDI‐MatWerk Ontology (MWO), a Basic Formal Ontology‐based framework for interoperable research data management in materials science and engineering (MSE). Covering consortium structures, research data management resources, services, and instruments, MWO enables semantic integration, Findable, Accessible, Interoperable, and ...
Hossein Beygi Nasrabadi +4 more
wiley +1 more source
Towards Defect Phase Diagrams: From Research Data Management to Automated Workflows
Advanced Engineering Materials, EarlyView.A research data management infrastructure is presented for the systematic integration of heterogeneous experimental and simulation data required for defect phase diagrams. The approach combines openBIS with a companion application for large‐object storage, automated metadata extraction, provenance tracking and federated data access, thereby supporting ...
Khalil Rejiba +5 more
wiley +1 more source
Partially Supervised Named Entity Recognition via the Expected Entity Ratio Loss
Transactions of the Association for Computational Linguistics, 2021 We study learning named entity recognizers in the presence of missing entity annotations. We approach this setting as tagging with latent variables and propose a novel loss, the Expected Entity Ratio, to learn models in the presence of systematically ...
Thomas Effland, Michael Collins
doaj +1 more source
Named Entity Recognition in Twitter using Images and Text
, 2017 Named Entity Recognition (NER) is an important subtask of information extraction that seeks to locate and recognise named entities. Despite recent achievements, we still face limitations with correctly detecting and classifying entities, prominently in ...
Esteves, Diego +3 more
core +1 more source
Fostering Innovation: Streamlining Magnetocaloric Materials Research by Digitalization
Advanced Engineering Materials, EarlyView.Magnetocaloric cooling (MCE) is an environmentally friendly refrigeration method with great potential. Optimizing MCE materials involves the preparation and screening of large quantities of samples, which in turn generates a large amount of data. A digitalization approach is presented that uses ontologies, knowledge graphs, and digital workflows to ...
Simon Bekemeier +17 more
wiley +1 more source
Improving Multilingual Named Entity Recognition with Wikipedia Entity Type Mapping
, 2016 The state-of-the-art named entity recognition (NER) systems are statistical machine learning models that have strong generalization capability (i.e., can recognize unseen entities that do not appear in training data) based on lexical and contextual ...
Florian, Radu, Ni, Jian
core +1 more source
Reranking for biomedical named-entity recognition [PDF]
Proceedings of the Workshop on BioNLP 2007 Biological, Translational, and Clinical Language Processing - BioNLP '07, 2007 This paper investigates improvement of automatic biomedical named-entity recognition by applying a reranking method to the COLING 2004 JNLPBA shared task of bioentity recognition. Our system has a common reranking architecture that consists of a pipeline of two statistical classifiers which are based on log-linear models.
Kazuhiro Yoshida, Jun'ichi Tsujii
openaire +2 more sources
PASTA‐ELN: Simplifying Research Data Management for Experimental Materials Science
Advanced Engineering Materials, EarlyView.Research data management faces ongoing hurdles as many ELNs remain complex and restrictive. PASTA‐ELN offers an open‐source, cross‐platform solution that prioritizes simplicity, offline access, and user control. Its in tuitive folder structure, modular Python add‐ons, and open formats enable seamless documentation, FAIR data practices, and easy ...
S. Brinckmann, G. Winkens, R. Schwaiger
wiley +1 more source