Results 21 to 30 of about 292 (213)
Jointly Embedding Entities and Text with Distant Supervision [PDF]
Proceedings of The Third Workshop on Representation Learning for NLP, 2018 12 pages; Accepted to 3rd Workshop on Representation Learning for NLP (Repl4NLP 2018).
Newman-Griffis, D. +2 more
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Learning to Rationalize for Nonmonotonic Reasoning with Distant Supervision
Proceedings of the AAAI Conference on Artificial Intelligence, 2021 The black-box nature of neural models has motivated a line of research that aims to generate natural language rationales to explain why a model made certain predictions. Such rationale generation models, to date, have been trained on dataset-specific crowdsourced rationales, but this approach is costly and is not generalizable to new tasks and domains.
Faeze Brahman +3 more
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IEEE Access, 2020 Recent advances in deep neural networks (DNNs) have enabled us to achieve reliable named entity recognition (NER) models without handcrafting features. However, these are also some obstacles imposed by using those machine learning methods, in need of a ...
Dezheng Zhang +6 more
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Distant Supervision for Extractive Question Summarization [PDF]
, 2020 Questions are often lengthy and difficult to understand because they tend to contain peripheral information. Previous work relies on costly human-annotated data or question-title pairs. In this work, we propose a distant supervision framework that can train a question summarizer without annotation costs or question-title pairs, where sentences are ...
Tatsuya Ishigaki +4 more
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Chemical-induced disease relation extraction via attention-based distant supervision
BMC Bioinformatics, 2019 Background Automatically understanding chemical-disease relations (CDRs) is crucial in various areas of biomedical research and health care. Supervised machine learning provides a feasible solution to automatically extract relations between biomedical ...
Jinghang Gu +3 more
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Boosting Knowledge Base Automatically via Few-Shot Relation Classification
Frontiers in Neurorobotics, 2020 Relation classification (RC) aims at extracting structural information, i.e., triplets of two entities with a relation, from free texts, which is pivotal for automatic knowledge base construction. In this paper, we investigate a fully automatic method to
Ning Pang +3 more
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Distant Supervision from Knowledge Graphs [PDF]
, 2018 In this chapter, we discuss approaches leveraging distant supervision for relation extraction. We start by introducing the key ideas behind distant supervision as well as their main shortcomings. We then discuss approaches that improve over the basic method, including approaches based on the at-least-one-principle along with their extensions for ...
Smirnova, Alisa +2 more
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An Attention-Based Model Using Character Composition of Entities in Chinese Relation Extraction
Information, 2020 Relation extraction is a vital task in natural language processing. It aims to identify the relationship between two specified entities in a sentence. Besides information contained in the sentence, additional information about the entities is verified to
Xiaoyu Han +3 more
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Iterative Annotation of Biomedical NER Corpora with Deep Neural Networks and Knowledge Bases
Applied Sciences, 2022 The large availability of clinical natural language documents, such as clinical narratives or diagnoses, requires the definition of smart automatic systems for their processing and analysis, but the lack of annotated corpora in the biomedical domain ...
Stefano Silvestri +2 more
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Learning To Recognize Procedural Activities with Distant Supervision
2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022 In this paper we consider the problem of classifying fine-grained, multi-step activities (e.g., cooking different recipes, making disparate home improvements, creating various forms of arts and crafts) from long videos spanning up to several minutes.
Xudong Lin 0003 +5 more
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