From 9fc59c1ea0a5fd60026ad38b2783d3ecf755e374 Mon Sep 17 00:00:00 2001
From: guillaume-millot <90203812+guillaume-millot@users.noreply.github.com>
Date: Wed, 1 May 2024 11:11:01 +0200
Subject: [PATCH] Update README.md

---
 eval/README.md | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/eval/README.md b/eval/README.md
index d291901..993563a 100644
--- a/eval/README.md
+++ b/eval/README.md
@@ -2,7 +2,7 @@
 
 ## Setup
 
-To run the evaluation scripts, we need some additional requirements that are not listed in the project dependencies.
+To run the evaluation scripts, you need some additional requirements that are not listed in the project dependencies.
 
 ```
 apt-get install wkhtmltopdf
@@ -12,7 +12,7 @@ apt-get install wkhtmltopdf
 
 First, you need to generate evaluation data with the `eval_table_extraction.py` script. This script will iterate through several reports and apply the set of table extraction algorithms you provided in your yaml configuration. 
 
-As an example, you might select the pages in the report from their filename and then apply several table extraction algorithms. Check out `configs/eval_table_extraction.yaml` for a suitable evaluation script.
+Check out `configs/eval_table_extraction.yaml` for a suitable yaml configuration.
 
 You can then call the script as :
 
@@ -37,6 +37,6 @@ To run the application, it is as simple as :
 streamlit run eval/eval_app.py eval/data/data_step2_before-currency-unit_eval.csv
 ```
 
-`data_step2_before-currency-unit_eval.csv` is a cleaned up version of the `data_step2_before-currency-unit.csv` file which contains reference data extracted and manually cleaned up by the team.
+`data_step2_before-currency-unit_eval.csv` is a cleaned up version of the `data_step2_before-currency-unit.csv` file which contains reference data extracted and manually cleaned up by the TaxObservatory team.
 
-At launch, you will be requested to provide a pickle file with extracted data. You might select `eval_20240408_200249.plk` in the `eval/data/` directory. It contains extracted tables for multiple reports and extractions and is a great way to get started.
+At launch, you will be requested to provide a pickle file with extracted data. You might select `eval_20240408_200249.plk` from the `eval/data/` directory. It contains extracted tables for multiple reports and extractions and is a great way to get started.