foreign language text, it does not always deliver accurate translations, and most times it tends to repeat verbatim the same word it is expected to translate. Grammatically, for example, Google Translate struggles to differentiate between imperfect and perfect aspects in Romance languages so habitual and continuous acts in the past often become single historical events. Although seemingly pedantic, this can often lead to incorrect results (to a native speaker of for example French and Spanish) which would have been avoided by a human translator. Knowledge of the subjunctive mood is virtually non-existent. Moreover, the formal second person () is often chosen, whatever the context or accepted usage. Since its English reference material contains only "you" forms, it has difficulty translating a language with "you all" or formal "you" variations. Due to differences between languages in investment, research, and the extent of digital resources, the accuracy of Google Translate varies greatly among languages. Some languages produce better results than others. Most languages from Africa, Asia, and the Pacific, tend to score poorly in relation to the scores of many well-financed European languages, Afrikaans and Chinese being the high-scoring exceptions from their continents. No languages indigenous to Australia are included within Google Translate. Higher scores for European can be partially attributed to the Europarl Corpus, a trove of documents from the European Parliament that have been professionally translated by the mandate of the European Union into as many as 21 languages. A 2010 analysis indicated that French to English translation is relatively accurate, and 2011 and 2012 analyses showed that Italian to English translation is relatively accurate as well. However, if the source text is shorter, rule-based machine translations often perform better; this effect is particularly evident in Chinese to English translations. While edits of translations may be submitted, in Chinese specifically one cannot edit sentences as a whole. Instead, one must edit sometimes arbitrary sets of characters, leading to incorrect edits. A good example is Russian-to-English. Formerly one would use Google Translate to make a draft and then use a dictionary and common sense to correct the numerous mistakes. As of early 2018 Translate is sufficiently accurate to make the Russian Wikipedia accessible to those who can read English. The quality of Translate can be checked by adding it as an extension to Chrome or Firefox and applying it to the left language links of any Wikipedia article. It can be