Extraction, selection and distribution of meaning elements for monolingual information tools

In this contribution, we analyze concrete user needs in reception situations based on concrete text examples. The point of departure is that a potential dictionary user reads a text and does not understand a word or a fixed expression, and therefore he seeks help in an information tool. Our topic is how lexicographers can provide the kind of help that the dictionary user needs to solve his reception problem. In order to do this, our starting point is not: “encyclopedic items do not belong to dictionaries” or “you always have to follow a certain schema for meaning explanations”. The starting point is: what meaning elements are needed to give the dictionary user the help he seeks (here: understand a word)? And how could and should these meaning elements be incorporated, i.e. formulated and presented, in the dictionary article? Having user needs as our focus point, we try to isolate and extract data elements from a text corpus, in which we find a number of text examples, collocations, synonyms, links, images etc. Among these different types of data, we select a number of meaning elements; these meaning elements could be presented in one field (the meaning field), but in many cases they are distributed into different parts of a dictionary entry, e.g. links, lexical remarks and synonym remarks. This distribution as well as the formulation of the meaning elements will depend on the user and his needs

Epistemology · Information retrieval · Linguistics · Natural language processing · Text corpus · User needs · Computer Science · Lexicography and Language Studies · linguistics and terminology studies · Mathematics · Natural Language Processing Techniques · Philosophy · Artificial Intelligence

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