Update README.md

README.md

@@ -10,20 +10,19 @@ multilinguality:
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 ## Every Prompt
-Every Prompt is a data driven approach to mine instructions from the web.
-It contains more than million FAQs and HowTos from all around the world in the structured format.
+Every Prompt is a data-driven approach to mining instructions from the web.
+It contains over a million FAQs and HowTos from around the world in a structured format.
 It also has basic pre-processing to calculate the length of the useful text and identify the language of that text with the help of [GCLD3](https://github.com/google/cld3)
 
 It relies on the [Web Data Commons](http://webdatacommons.org) dataset to find the seed list of sites with [**HowTo**](https://schema.org/HowTo) and [**FAQPage**](https://schema.org/FAQPage) items.
 The general pipeline looks like this:
 * Download 1.6TB of structured data from webdatacommons to identify the pages with the structured data we need (wget/parallel). That gives us 1,985,925 seed pages
-* Crawls the seed pages and tries to extract structured data using [extruct](https://pypi.org/project/extruct/#description) package. That lefts around 1,358,638 pages which are alive and well-formed.
+* Crawls the seed pages and tries to extract structured data using [extruct](https://pypi.org/project/extruct/#description) package. That left around 1,358,638 pages which are alive and well-formed.
 * Extracts only the relevant structured data of the HowTo/FAQPage type with the help of jmespath. That boils down to 1,266,926 json documents.
-* Extracts the textual information out of the structure to identify the language of the text, length of the textual data and the text/data ratio.
+* Extracts the textual information out of the structure to identify the text's language, the textual data's length, and the text/data ratio.
 
-The resulting dataset you can use by applying the filtering on the language and amount of the text. You need to convert the structured data into instructions yourself.
-You'll need to apply extra cleansing/evaluation of the instructions you've got because you know, internet is still full of crap
+You can use the resulting dataset by filtering for the language and amount of the text. You need to convert the structured data into instructions yourself.
+You'll need to apply extra cleansing/evaluation of the instructions you've got because, you know, the internet is still full of crap.
 
 ## License
-**Code** of the project has MIT license.
-
+**Code** of the project has an MIT license.