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In the article “Locating Place Names At Scale: Using Natural Language Processing To Identify Geographical Information In Text” by Lauren Tilton, the author speaks about the notion of understanding historical data differently by using programming to look at the data in a broader context. The author gives the example of names of geographic places, how at first glance a historical piece of data reading Paris could mean Paris, France or Paris, Texas and with the help of broader context we are able to deduce which is which. Computer programming has worked to streamline this process by using Named Entity Recognition (NER), a natural language processing technique, and applying it to interviews taken of American experiences during the New Deal to help to give a broader understanding of movement and place in America. I echo DA’s sentiments which they say, “I think this article was a great way to explore the fault in some programming and show how searching for specific things does not always get you the results you need. Sometimes we need to look outside what we are actually looking for.”