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To score well in RTE3, and even more so to create good justifications for entailments, substantial lexical and world knowledge is needed. With this in mind, we present an analysis of a sample of the RTE3 positive entailment pairs, to identify where and what kinds of world knowledge are needed to fully identify and justify the entailment, and discuss several(More)
Our goal is to be able to answer questions about text that go beyond facts explicitly stated in the text, a task which inherently requires extracting a " deep " level of meaning from that text. Our approach treats meaning processing fundamentally as a modeling activity, in which a knowledge base of common-sense expectations guides interpretation of text,(More)
One of the big challenges in understanding text, i.e., constructing an overall coherent representation of the text, is that much information needed in that representation is unstated (implicit). Thus, in order to "fill in the gaps" and create an overall representation , language processing systems need a large amount of world knowledge, and creating those(More)
While there has been tremendous progress in automatic database population in recent years, most of human knowledge does not naturally fit into a database form. For example, knowledge that "metal objects can conduct electricity" or "animals grow fur to help them stay warm" requires a substantially different approach to both acquisition and representation.(More)
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 biological processes would dramatically improve the performance of semantic applications involving inference such as question answering (QA) – specifically " How? " and " Why? "(More)
Urethane test objects are available that are more durable than traditional gel-based objects. Their ultrasound (US) propagation speed differs from scanner calibration velocity. This is clearly a disadvantage in checking caliper accuracy, but its effect on other measurements such as resolution is not well known. A test object containing a column of nylon(More)
Recent advances in question answering from text have shown that information retrieval, natural language processing and machine learning techniques can go a long way in retrieving answers to certain types of questions from large bodies of text. Questions requiring more reasoning and inference, or those whose answers require synthesis or explanation are more(More)