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For the reading “Locating Place Names At Scale: Using Natural Language Processing To Identify Geographical Information In Text”, I mostly was focused on the visualizations shown and also thought about the importance of knowing specification. Using text with a lack of specification has potential to cause real errors in data taken from that text, which is why NER (Named Entity Recognition) seems extremely important and useful to me in terms of collecting data from text. I liked both of the visualizations presented in this article because they were clear and easy to see, and centered on a specific location. However, I would be interested to see how both of these visualizations would look if the entire country was in the picture. The two questions posed in the post by TB intrigued me: “What if the location found is not what it seems to be? Does the algorithm discard the term if there is too much ambiguity?”. While it is useful and important, there are definitely possible problems that come to mind when reading about this process.