Most existing joint neural models for Information Extraction (IE) use local task-specific
classifiers to predict labels for individual instances (eg, trigger, relation) regardless of their …

A survey of computational methods for understanding, generating, and manipulating human
language, which offers a synthesis of classical representations and algorithms with …

Existing works on information extraction (IE) have mainly solved the four main tasks
separately (entity mention recognition, relation extraction, event trigger detection, and …

Event schema depicts the typical structure of complex events, serving as a scaffolding to
effectively analyze, predict, and possibly intervene in the ongoing events. To induce event …

With the increased advancements in technology and the emergence of different kinds of
applications, the amount of available data becomes enormous, and the large proliferation of …

Coreference resolution for event mentions enables extraction systems to process document-
level information. Current systems in this area base their decisions on rich semantic features …

This monograph proposes a comprehensive and fully automatic approach to designing text
analysis pipelines for arbitrary information needs that are optimal in terms of run-time …

In this paper we describe a joint effort by the City University of New York (CUNY), University
of Illinois at Urbana-Champaign (UIUC) and SRI International at participating in the mono …

We present a fully automatic system from raw data gathering to navigation over
heterogeneous news sources, including over 18k hours of broadcast video news, 3.58 M …

There is an increased interest in solving complex constrained problems where part of the
input is not given as facts, but received as raw sensor data such as images or speech. We …