Stephen Helmreich

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Although understanding health information is important, the texts provided are often difficult to understand. There are formulas to measure readability levels, but there is little understanding of how linguistic structures contribute to these difficulties. We are developing a toolkit of linguistic metrics that are validated with representative users and can(More)
This paper describes a multi-site project to annotate six sizable bilingual parallel corpora for interlingual content. After presenting the background and objectives of the effort, we will go on to describe the data set that is being annotated, the interlingua representation language used, an interface environment that supports the annotation task and the(More)
An unprecedented combination of simula-tive and metaphor based reasoning about beliefs is achieved in an AI system, ATT-Meta. Much mundane discourse about beliefs productively uses conceptual metaphors such as MIND AS CONTAINER and IDEAS AS INTERNAL UTTERANCES, and ATT-Meta's metaphor-based reasoning accordingly leads to crucial discourse comprehension(More)
Millions of laypersons need more medical information than they are customarily provided during their doctor's visit. Health websites can help fill this knowledge gap, but the text is believed to be too difficult to understand for many laypersons. To help write text that is not perceived as too difficult and leads to better comprehension (actual difficulty),(More)
Machine Readable Dictionaries (MRDs) contain much useful information about lan£uage. Researchers have worked for the last decade on ways to extract this information for language processing systems. But processing dictionaries for use in natural language computation is itself a difficult problem. Transforming information from a version designed for human(More)
The IAMTC project (Interlingual Annotation of Multilingual Translation Corpora) is developing an interlingual representation framework for annotation of parallel corpora (English paired with Arabic, French, Hindi, Japanese, Korean, and Spanish) with deep-semantic representations. In particular, we are investigating meaning equivalent paraphrases involving(More)
This paper focuses on an important step in the creation of a system of meaning representation and the development of semantically annotated parallel corpora, for use in applications such as machine translation, question answering, text summarization, and information retrieval. The work described below constitutes the first effort of any kind to annotate(More)
MT systems that use only superficial representations, including the current generation of statistical MT systems, have been successful and useful. However, they will experience a plateau in quality, much like other " silver bullet " approaches to MT. We pursue work on the development of interlingual representations for use in symbolic or hybrid MT systems.(More)