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We describe MITRE's two submissions to the RTE Challenge, intended to exemplify two different ends of the spectrum of possibilities. The first submission is a traditional system based on linguistic analysis and inference, while the second is inspired by alignment approaches from machine translation. We also describe our efforts to build our own entailment(More)
OBJECTIVE De-identified medical records are critical to biomedical research. Text de-identification software exists, including "resynthesis" components that replace real identifiers with synthetic identifiers. The goal of this research is to evaluate the effectiveness and examine possible bias introduced by resynthesis on de-identification software. (More)
Introduction Collaborative environments have grown quite sophisticated over the years. They have evolved from simple text conferencing tools [2] to full suites of integrated multi-modal tools such as Habanero [9] or MITRE's room-based Collaborative Virtual Workspace [3, 4]. As a result, evaluating multi-modal collaborative systems is an order of magnitude(More)
communications (HPCC) technology. The user environment for this project is K-12 education , which offers a range of electronically connecte d users with a rich variety of uses. AskERIC, one o f the project's research partners, currently provides a Smithsonian award-nominated question-answerin g service to K-12 educators through the Internet vi a expert(More)
PURPOSE Medical records must often be stripped of patient identifiers, or de-identified, before being shared. De-identification by humans is time-consuming, and existing software is limited in its generality. The open source MITRE Identification Scrubber Toolkit (MIST) provides an environment to support rapid tailoring of automated de-identification to(More)
This paper presents an overview of the knowledge representation facilities of King Kong a transportable natural language system. The thrust of the paper is towards demonstrating how the particulars of Kong's representation language support the processing of key phenomena of natural language. To this extent, we cover Kong's terminological hierarchies; the(More)
We describe an experiment to elicit judgments on the validity of gene-mutation relations in MEDLINE abstracts via crowdsourcing. The bio-medical literature contains rich information on such relations, but the correct pairings are difficult to extract automatically because a single abstract may mention multiple genes and mutations. We ran an experiment(More)
In this paper, we will describe work in progress at the MITRE Corporation on embedding speech-enabled interfaces in Web browsers. This research is part of our work to establish the infrastructure to create Web-hosted versions of prototype multimodal interfaces, both intelligent and otherwise. Like many others, we believe that the Web is the best potential(More)
PURPOSE We describe an experiment to build a de-identification system for clinical records using the open source MITRE Identification Scrubber Toolkit (MIST). We quantify the human annotation effort needed to produce a system that de-identifies at high accuracy. METHODS Using two types of clinical records (history and physical notes, and social work(More)
We describe a novel method for detecting errors in task-based human-computer (HC) dialogues by automatically deriving them from semantic tags. We examined 27 HC dialogues from the DARPA Communicator air travel domain, comparing user inputs to system responses to look for slot value discrepancies, both automatically and manually. For the automatic method, we(More)