Ambiguity, the phenomenon that a word has more than one sense, poses difficulties for many current Natural Language Processing (NLP) systems. Algorithms that assist in the resolution of these ambiguities, i.e. which make unambiguous a word, or more generally, a text string, will boost performance of these systems. To test such techniques in the biomedical language domain, we have developed a Wo...

Word sense disambiguation (WSD) is important to many application problems in natural language processing fields. It plays a very important role in information retrieval systems, machine translation systems, text classification systems and automatic summarization systems. Its task is to automatically choose the intended sense of an ambiguous word in a given context. In this paper, a new supervis...

State of the art Word Sense Disambiguation (WSD) systems require large sense-tagged corpora along with lexical databases to reach satisfactory results. The number of English language resources for developed WSD increased in the past years, while most other languages are still under-resourced. The situation is no different for Dutch. In order to overcome this data bottleneck, the DutchSemCor pro...

The role of peripheral sense organs and muscles in specifying the circuitry of the central nervous system during ontogeny was tested in larval lobsters. Presumptive locomotor appendages, the abdominal swimmerets, were extirpated before their differentiation. Electrophysiological recordings made 2-4 weeks later from the corresponding motor nerves showed that, despite the absence of the target mu...

The aim of this study is to explore the word sense disambiguation (WSD) problem across two biomedical domains-biomedical literature and clinical notes. A supervised machine learning technique was used for the WSD task. One of the challenges addressed is the creation of a suitable clinical corpus with manual sense annotations. This corpus in conjunction with the WSD set from the National Library...

Vector Based Text Classification in the Question Answering field has long been explored. However, there has not been any attempt so far to take word senses into consideration in the development of the feature sets in the classifier. This paper aims to investigate the performance of a question answering text classifier built using not just the root form of words but also taking the senses of tho...