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Open Information Extraction from the Web
TLDR
Open IE (OIE), a new extraction paradigm where the system makes a single data-driven pass over its corpus and extracts a large set of relational tuples without requiring any human input, is introduced.
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Identifying Relations for Open Information Extraction
TLDR
Two simple syntactic and lexical constraints on binary relations expressed by verbs are introduced in the ReVerb Open IE system, which more than doubles the area under the precision-recall curve relative to previous extractors such as TextRunner and woepos.
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Named Entity Recognition in Tweets: An Experimental Study
TLDR
The novel T-ner system doubles F1 score compared with the Stanford NER system, and leverages the redundancy inherent in tweets to achieve this performance, using LabeledLDA to exploit Freebase dictionaries as a source of distant supervision.
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Open Language Learning for Information Extraction
Open Information Extraction (IE) systems extract relational tuples from text, without requiring a pre-specified vocabulary, by identifying relation phrases and associated arguments in arbitrary…
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Web document clustering: a feasibility demonstration
TLDR
To satisfy the stringent requirements of the Web domain, an incremental, linear time algorithm called Suffix Tree Clustering (STC) is introduced which creates clusters based on phrases shared between documents, showing that STC is faster than standard clustering methods in this domain.
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Extracting Product Features and Opinions from Reviews
TLDR
Opine is introduced, an unsupervised information-extraction system which mines reviews in order to build a model of important product features, their evaluation by reviewers, and their relative quality across products.
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Unsupervised named-entity extraction from the Web: An experimental study
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Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge
TLDR
A new question set, text corpus, and baselines assembled to encourage AI research in advanced question answering constitute the AI2 Reasoning Challenge (ARC), which requires far more powerful knowledge and reasoning than previous challenges such as SQuAD or SNLI.
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CORD-19: The COVID-19 Open Research Dataset
TLDR
The mechanics of dataset construction are described, highlighting challenges and key design decisions, an overview of how CORD-19 has been used, and several shared tasks built around the dataset are described.
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Web-scale information extraction in knowitall: (preliminary results)
TLDR
KnowItAll, a system that aims to automate the tedious process of extracting large collections of facts from the web in an autonomous, domain-independent, and scalable manner, is introduced.
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