diff --git a/examples/openspending/content/stories/where-the-european-structural-and-investment-funds-go.mdx b/examples/openspending/content/stories/where-the-european-structural-and-investment-funds-go.mdx
index 2026cf02..31bec979 100644
--- a/examples/openspending/content/stories/where-the-european-structural-and-investment-funds-go.mdx
+++ b/examples/openspending/content/stories/where-the-european-structural-and-investment-funds-go.mdx
@@ -8,16 +8,16 @@ European Structural and Investment Funds (ESIF) is a financial instrument used b
In this data story, our objective is to determine which country benefits the most from the ESIF funds and identify the region within the EU that receives the highest amount of funding.
-To begin our analysis, we are using data on the allocation of ESIF funds across EU member states and their respective regions. These dataset are provided by previous work at OpenSpending project. See available datasets:
+To begin our analysis, we are using data on the allocation of ESIF funds across EU member states and their respective regions. These datasets are provided by previous work at OpenSpending project. See available datasets:
- Full dataset: https://www.openspending.org/@os-data/complete-european-esif-funds-beneficiaries-2007-2020
- By country, e.g., this is for Austria: https://www.openspending.org/@os-data/complete-european-esif-funds-beneficiaries-2007-2020-filtered-by-at
-The data provides insights into the financial assistance provided by the European Union to support regional development and economic cohesion:
+The data provide insights into the financial assistance provided by the European Union to support regional development and economic cohesion:
-After processing the available datasets we have derived an aggregated data resource that groups data by country which enables us to understand where is the most funding went between 2007 and 2020. Notice that maximum amounts in each column are highlighted in the table but they might be in local currencies so check the 'currency' field:
+After processing the available datasets we have derived an aggregated data resource that groups data by country which enables us to understand where the most funding went between 2007 and 2020. Notice that maximum amounts in each column are highlighted in the table but they might be in local currencies so check the 'currency' field: