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Some examples of commonly used question answering datasets include TruthfulQA, Web Questions, TriviaQA, and SQuAD. [127] Evaluation datasets may also take the form of text completion, having the model select the most likely word or sentence to complete a prompt, for example: "Alice was friends with Bob. Alice went to visit her friend, ____". [1]
The first published English grammar was a Pamphlet for Grammar of 1586, written by William Bullokar with the stated goal of demonstrating that English was just as rule-based as Latin. Bullokar's grammar was faithfully modeled on William Lily's Latin grammar, Rudimenta Grammatices (1534), used in English schools at that time, having been ...
These models take text prompts as input and use them to generate AI-generated images. Text-to-image models typically do not understand grammar and sentence structure in the same way as large language models, [48] thus may require a different set of prompting techniques. Text-to-image models do not natively understand negation.
A famous example for lexical ambiguity is the following sentence: "Wenn hinter Fliegen Fliegen fliegen, fliegen Fliegen Fliegen hinterher.", meaning "When flies fly behind flies, then flies fly in pursuit of flies." [40] [circular reference] It takes advantage of some German nouns and corresponding verbs being homonymous. While not noticeable ...
The AI programs first adapted to simulate both natural and artificial grammar learning used the following basic structure: Given A set of grammatical sentences from some language. Find A procedure for recognizing and/or generating all grammatical sentences in that language. An early model for AI grammar learning is Wolff's SNPR System.
In linguistics and grammar, a sentence is a linguistic expression, such as the English example "The quick brown fox jumps over the lazy dog." In traditional grammar , it is typically defined as a string of words that expresses a complete thought, or as a unit consisting of a subject and predicate .
Grammarly is an English language writing assistant software tool. It reviews the spelling, grammar, and tone of a piece of writing as well as identifying possible instances of plagiarism . It can also suggest style and tonal recommendations to users and produce writing from prompts with its generative AI capabilities.
Despite this, GPT-2 achieved 5 BLEU on the WMT-14 English-to-French test set (slightly below the score of a translation via word-for-word substitution). It was also able to outperform several contemporary (2017) unsupervised machine translation baselines on the French-to-English test set, where GPT-2 achieved 11.5 BLEU.