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Convolutional 2D Knowledge Graph Embeddings
Link prediction for knowledge graphs is the task of predicting missing relationships between entities. Previous work on link prediction has focused on shallow, fast models which can scale to largeExpand
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brat: a Web-based Tool for NLP-Assisted Text Annotation
We introduce the brat rapid annotation tool (BRAT), an intuitive web-based tool for text annotation supported by Natural Language Processing (NLP) technology. BRAT has been developed for richExpand
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Constructing Datasets for Multi-hop Reading Comprehension Across Documents
Most Reading Comprehension methods limit themselves to queries which can be answered using a single sentence, paragraph, or document. Enabling models to combine disjoint pieces of textual evidenceExpand
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Neural Architectures for Fine-grained Entity Type Classification
In this work, we investigate several neural network architectures for fine-grained entity type classification. Particularly, we consider extensions to a recently proposed attentive neuralExpand
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An Attentive Neural Architecture for Fine-grained Entity Type Classification
In this work we propose a novel attention-based neural network model for the task of fine-grained entity type classification that unlike previously proposed models recursively composesExpand
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Wronging a Right: Generating Better Errors to Improve Grammatical Error Detection
Grammatical error correction, like other machine learning tasks, greatly benefits from large quantities of high quality training data, which is typically expensive to produce. While writing a programExpand
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Task-Oriented Learning of Word Embeddings for Semantic Relation Classification
We present a novel learning method for word embeddings designed for relation classification. Our word embeddings are trained by predicting words between noun pairs using lexical relation-specificExpand
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Jointly Learning Word Representations and Composition Functions Using Predicate-Argument Structures
We introduce a novel compositional language model that works on PredicateArgument Structures (PASs). Our model jointly learns word representations and their composition functions using bagof-wordsExpand
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UCL Machine Reading Group: Four Factor Framework For Fact Finding (HexaF)
In this paper we describe our 2 place FEVER shared-task system that achieved a FEVER score of 62.52% on the provisional test set (without additional human evaluation), and 65.41% on the developmentExpand
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Leveraging Monolingual Data for Crosslingual Compositional Word Representations
In this work, we present a novel neural network based architecture for inducing compositional crosslingual word representations. Unlike previously proposed methods, our method fulfills the followingExpand
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