Natural language processing in the faq finder system: Results and prospects

Abstract This paper describes some recent results regarding the employment of natural language processing techniques in the FAQ FINDER system. FAQ FINDER is a natural language question-answering system that uses files of frequently-asked questions as its knowledge base. Unlike AI questionanswering systems that focus on the generation of new answers, FAQ FINDER retrieves existing ones found in frequently-asked question files. FAQ FINDER uses a combination of statistical and natural language techniques to match user questions against known question/answer pairs from FAQ files. We strove in our experiments to identify the contribution of these techniques to the overall success of the system. One unexpected result was that our parsing technique was not contributing as much to the system's performance as we expected. We discuss some of the reasons why this may have been the case, and describe further natural language processing research designed to address the system's current needs

The role of hydrogen and fuel cells in the global energy system

Hydrogen technologies have experienced cycles of excessive expectations followed by disillusion. Nonetheless, a growing body of evidence suggests these technologies form an attractive option for the deep decarb onisation of global energy systems, and that recent improvements in their cost and performance point towards economic viability as well. This paper is a comprehensive review of the potential role that hydrogen could play in the provision of electricity, h eat, industry, transport and energy storage in a low - carbon energy system, and an assessment of the status of hydrogen in being able to fulfil that potential. The picture that emerges is one of qualified promise: hydrogen is well established in certain nic hes such as forklift trucks, while mainstream applications are now forthcoming. Hydrogen vehicles are available commercially in several countries, and 225,000 fuel cell home heating systems have been sold. This represents a step change from the situation of only five years ago. This review shows that challenges around cost and performance remain, and considerable improvements are still required for hydrogen to become truly competitive. But such competitiveness in the medium - term future no longer seems an unrealistic prospect, which fully justifies the growing interest and policy support for these technologies around the world

Tree-cut and A Lexicon based on Systematic Polysemy

This paper describes a lexicon organized around systematic polysemy: a set of word senses that are related in systematic and predictable ways. The lexicon is derived by a fully automatic extraction method which utilizes a clustering technique called tree-cut. We compare our lexicon to WordNet cousins, and the inter-annotator disagreement observed between WordNet Semcor and DSO corpora

Maximizing Top-down Constraints for Unification-based Systems

A left-corner parsing algorithm with topdown filtering has been reported to show very efficient performance for unificationbased systems. However, due to the nontermination of parsing with left-recursive grammars, top-down constraints must be weakened. In this paper, a general method of maximizing top-down constraints is proposed

Semi-automatic Induction of Systematic Polysemy from WordNet

This paper describes a semi-automatic method of inducing underspecified semantic classes from WordNet verbs and nouns. A underspecifie