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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.
A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. Prompt engineering may involve phrasing a query, specifying a style, choice of words and grammar, [ 3 ] providing relevant context, or describing a character for the AI to mimic.
The CBOW can be viewed as a ‘fill in the blank’ task, where the word embedding represents the way the word influences the relative probabilities of other words in the context window. Words which are semantically similar should influence these probabilities in similar ways, because semantically similar words should be used in similar contexts.
The logogen model of 1969 is a model of speech recognition that uses units called "logogens" to explain how humans comprehend spoken or written words. Logogens are a vast number of specialized recognition units, each able to recognize one specific word. This model provides for the effects of context on word recognition.
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 ...
[citation needed] The whole basis of language generation is through the training of computer models and algorithms which can learn from a large dataset of information. For example, there are mixed sentence models which tend to perform better as they take a larger sampling size of sentenced data rather than just words [10]. These models ...
The underlying hypothesis of this approach is that, words are semantically similar if they appear in similar documents, with in similar context windows, or in similar syntactic contexts. [3] Each occurrence of a target word in a corpus is represented as a context vector. These context vectors can be either first-order vectors, which directly ...
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 .