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SemEval-2017 Task 5: Fine-Grained Sentiment Analysis on Financial Microblogs and News
TLDR
This paper discusses the “Fine-Grained Sentiment Analysis on Financial Microblogs and News” task as part of SemEval-2017, specifically under the“Detecting sentiment, humour, and truth” theme. Expand
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A Survey on Open Information Extraction
TLDR
We provide a detailed overview of the various approaches that were proposed to date to solve the task of Open Information Extraction. Expand
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Graphene: Semantically-Linked Propositions in Open Information Extraction
TLDR
We present an Open Information Extraction (IE) approach that uses a two-layered transformation stage consisting of a clausal disembedding layer and a phrasal dis embedding layer, together with rhetorical relation identification. Expand
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FinSSLx: A Sentiment Analysis Model for the Financial Domain Using Text Simplification
TLDR
This paper presents FinSSLx, a sentiment-based prediction model for the financial domain which uses the combination of a clausal/phrasal sentence simplification step for large-scale polarity lexical acquisition. Expand
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WWW'18 Open Challenge: Financial Opinion Mining and Question Answering
TLDR
The growing maturity of Natural Language Processing (NLP) techniques and resources is dramatically changing the landscape of many application domains which are dependent on the analysis of unstructured data at scale. Expand
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SemEval-2017 Task 11: End-User Development using Natural Language
TLDR
This task proposes a challenge to support the interaction between users and applications, micro-services and software APIs using natural language. Expand
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Transforming Complex Sentences into a Semantic Hierarchy
TLDR
We present an approach for recursively splitting and rephrasing complex English sentences into a novel semantic hierarchy of simplified sentences, with each of them presenting a more regular structure that may facilitate a wide variety of artificial intelligence tasks, such as machine translation (MT) or information extraction (IE). Expand
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A Compositional-Distributional Semantic Model for Searching Complex Entity Categories
TLDR
We propose a hybrid semantic model based on syntactic analysis, distributional semantics and named entity recognition to recognise paraphrases of entity categories. Expand
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A Framework for Evaluation of Machine Reading Comprehension Gold Standards
TLDR
We propose a unifying framework to systematically investigate the present linguistic features, required reasoning and background knowledge and factual correctness on one hand, and the presence of lexical cues as a lower bound for the requirement of understanding on the other hand. Expand
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Semantic Relation Classification: Task Formalisation and Refinement
TLDR
This work is in part funded by the SSIX Horizon 2020 project (grant agreement No 645425). Expand
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