Results 81 to 90 of about 631,702 (254)
Advanced Engineering Materials, EarlyView.Reproduction of stacking fault energy calculations from literature with a semi‐automated large language model‐assisted extraction procedure: extraction of simulation protocol, atomistic structures, computational parameters, and reported results, ontology alignment, knowledge graph construction and, finally, recomputation forvalidation.
Sepideh Baghaee Ravari +5 more
wiley +1 more source
Recognizing Textual Entailment Using a Machine Learning Approach
, 2010 We present our experiments on Recognizing Textual Entailment based on modeling the entailment relation as a classification problem. As features used to classify the entailment pairs we use a symmetric similarity measure and a non-symmetric similarity measure.
Miguel Ángel Ríos-Gaona +2 more
openaire +2 more sources
Advanced Engineering Materials, EarlyView.Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter +10 more
wiley +1 more source
Recognizing Textual Entailment Using Lexical Similarity
, 2008 We describe our participation in the PASCAL-2005 Recognizing Textual Entailment Challenge. Our method is based on calculating “directed ” sentence similarity: checking the directed “semantic” word overlap between the text and the hypothesis.
core
Paraphrase substitution for recognizing textual entailment [PDF]
, 2006 We describe a method for recognizing textual entailment that uses the length of the longest common subsequence (LCS) between two texts as its decision criterion.
Bosma, W.E., Callison-Burch, C.
core
Advanced Engineering Materials, EarlyView.The OntOMat ontology establishes a structured framework for polymer matrix fiber reinforced composite materials, integrating manufacturing processes, characterization methods, and multiscale design through the VDI/VDE 3682 formalized process description standard.
Nicolas Christ +19 more
wiley +1 more source
Recognizing Textual Entailment in Twitter Using Word Embeddings [PDF]
Proceedings of the 2nd Workshop on Evaluating Vector Space
Representations for NLP, 2017 In this paper, we investigate the application of machine learning techniques and word embeddings to the task of Recognizing Textual Entailment (RTE) in Social Media. We look at a manually labeled dataset consisting of user generated short texts posted on Twitter (tweets) and related to four recent media events (the Charlie Hebdo shooting, the Ottawa ...
openaire +2 more sources
Recognizing Textual Entailment Is lexical similarity enough?
, 2008 . We describe the system we used at the PASCAL-2005 Recognizing Textual Entailment Challenge. Our method for recognizing entailment is based on calculating “directed ” sentence similarity: checking the directed “semantic” word overlap between the text ...
Maarten De Rijke, Valentin Jijkoun
core
Advanced Engineering Materials, EarlyView.The community‐driven Platform MaterialDigital Core Ontology (PMDco) 3.0 is introduced as a Basic Formal Ontology‐aligned semantic backbone for the processing–structure–properties paradigm in Materials Science and Engineering. Modular engineering, automated releases, and validation workflows are highlighted and key semantic patterns for materials ...
Markus Schilling +15 more
wiley +1 more source
Is there a place for logic in recognizing textual entailment?
Linguistic Issues in Language Technology, 2014 From a purely theoretical point of view, it makes sense to approach recognizing textual entailment (RTE) with the help of logic. After all, entailment matters are all about logic. In practice, only few RTE systems follow the bumpy road from words to logic.
openaire +3 more sources