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This process will be sped up if creating sentences using multiple words from the list to construct sentences like "They think it is time to go" - "Ellos piensan que es hora de irse" in Spanish for instance. It is important to learn words in a given context and will make the words easier to remember.
However, parser generators for context-free grammars often support the ability for user-written code to introduce limited amounts of context-sensitivity. (For example, upon encountering a variable declaration, user-written code could save the name and type of the variable into an external data structure, so that these could be checked against ...
IWE combines Word2vec with a semantic dictionary mapping technique to tackle the major challenges of information extraction from clinical texts, which include ambiguity of free text narrative style, lexical variations, use of ungrammatical and telegraphic phases, arbitrary ordering of words, and frequent appearance of abbreviations and acronyms ...
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Recognition of these words is faster and more accurate than other words. The word frequency effect is one of the most robust and most commonly reported effects in contemporary literature on word recognition. It has played a role in the development of many theories, such as the bouma shape.
Context-free grammars are a special form of Semi-Thue systems that in their general form date back to the work of Axel Thue. The formalism of context-free grammars was developed in the mid-1950s by Noam Chomsky, [3] and also their classification as a special type of formal grammar (which he called phrase-structure grammars). [4]
Key Word In Context (KWIC) is the most common format for concordance lines. The term KWIC was coined by Hans Peter Luhn . [ 1 ] The system was based on a concept called keyword in titles , which was first proposed for Manchester libraries in 1864 by Andrea Crestadoro .
A weighted context-free grammar (WCFG) is a more general category of context-free grammar, where each production has a numeric weight associated with it. The weight of a specific parse tree in a WCFG is the product [7] (or sum [8]) of all rule weights in the tree. Each rule weight is included as often as the rule is used in the tree.