Events and entities are closely related; entities are often actors or participants in events and
events without entities are uncommon. The interpretation of events and entities is highly …

Please note that this manual describes the original Stanford Dependencies representation.
As of version 3.5. 2, the default representation output by the Stanford Parser and Stanford …

Abstract Machine reading calls for programs that read and understand text, but most current
work only attempts to extract facts from redundant web-scale corpora. In this paper, we focus …

Domain-specific knowledge graphs have emerged as a field unto their own, steadily and
perhaps not so slowly. Graphs have been pervasive in AI for a long period of time, dating …

We propose and implement a new approach, Document-Assisted Symbolic Execution
(DASE), to improve automated test generation and bug detection. DASE leverages natural …

To help learners foster collaboration and communication practices, Massive Open Online
Courses (MOOCs) have begun to incorporate a collaborative team-based learning …

Many name tagging approaches use local contextual information with much success, but fail
when the local context is ambiguous or limited. We present a new framework to improve …

Time is deeply woven into how people perceive, and communicate about the world. Almost
unconsciously, we provide our language utterances with temporal cues, like verb tenses …

Biological processes are complex phenomena involving a series of events that are related to
one another through various relationships. Systems that can understand and reason over …

Abstract Temporal Information Extraction (TIE) plays an important role in many natural
language processing and database applications. Temporal slot filling (TSF) is a new and …