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In the article “Locating Place Names At Scale: Using Natural Language Processing To Identify Geographical Information In Text”, the authors discuss how similarly named locations are identified using broad context without needing a human to decipher the text. Researchers use Named Entity Recognition (NER), which is a method that computers can use to process language, to locate names of places within text. They then start to find references to cities, states, or countries using Google API to narrow down the possibilities until there is only one left. If there is more than one possibility, whichever place is closest to the reference points is deemed correct. As DA put it, this article “explore[s] the fault in some programming” and data which is  a result of these faults. The article also demonstrates a way that people were able to circumvent these faults and create a solution.