Named Entity Recognition serves as the basis for many other areas in Information
Management. However, it is unclear what the meaning of Named Entity is, and yet there is a …

Information extraction suffers from its varying targets, heterogeneous structures, and
demand-specific schemas. In this paper, we propose a unified text-to-structure generation …

Entity matching refers to the task of determining whether two different representations refer
to the same real-world entity. It continues to be a prevalent problem for many organizations …

Event extraction (EE) is a crucial information extraction task that aims to extract event
information in texts. Previous methods for EE typically model it as a classification task, which …

Among different recommendation techniques, collaborative filtering usually suffer from
limited performance due to the sparsity of user-item interactions. To address the issues …

We present a new dataset and model for textual entailment, derived from treating multiple-
choice question-answering as an entailment problem. SciTail is the first entailment set that is …

In this paper we address the question of how to render sequence-level networks better at
handling structured input. We propose a machine reading simulator which processes text …

Recent years have witnessed a proliferation of large-scale knowledge bases, including
Wikipedia, Freebase, YAGO, Microsoft's Satori, and Google's Knowledge Graph. To increase …

The recently increased focus on misinformation has stimulated research in fact checking, the
task of assessing the truthfulness of a claim. Research in automating this task has been …

Two important aspects of semantic parsing for question answering are the breadth of the
knowledge source and the depth of logical compositionality. While existing work trades off …