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John Clark's Latin Verse Machine (1830–1843) is probably the first example of mechanised generative literature, [1] [2] while Christopher Strachey's love letter generator (1952) is the first digital example. [3] With the large language models (LLMs) of the 2020s, generative literature is becoming increasingly common.
Lexical choice is the subtask of Natural language generation that involves choosing the content words (nouns, non-auxiliary verbs, adjectives, and adverbs) in a generated text. Function words (determiners, for example) are usually chosen during realisation.
Wordnik has collected a corpus of billions of words which it uses to display example sentences, allowing it to provide information on a much larger set of words than a typical dictionary. Wordnik uses as many real examples as possible when defining a word. [1] [2]
A Diceware word list is any list of 6 5 = 7 776 unique words, preferably ones the user will find easy to spell and to remember. The contents of the word list do not have to be protected or concealed in any way, as the security of a Diceware passphrase is in the number of words selected, and the number of words each selected word could be taken ...
Drawing up a comprehensive list of words in English is important as a reference when learning a language as it will show the equivalent words you need to learn in the other language to achieve fluency. A big list will constantly show you what words you don't know and what you need to work on and is useful for testing yourself.
Above: An image classifier, an example of a neural network trained with a discriminative objective. Below: A text-to-image model, an example of a network trained with a generative objective. Since its inception, the field of machine learning used both discriminative models and generative models, to model and predict data.
Natural language generation (NLG) is a software process that produces natural language output. A widely-cited survey of NLG methods describes NLG as "the subfield of artificial intelligence and computational linguistics that is concerned with the construction of computer systems that can produce understandable texts in English or other human languages from some underlying non-linguistic ...
This facet of word2vec has been exploited in a variety of other contexts. For example, word2vec has been used to map a vector space of words in one language to a vector space constructed from another language. Relationships between translated words in both spaces can be used to assist with machine translation of new words. [27]