Update README.md

README.md

@@ -207,12 +207,12 @@ The high-level captions capture the human interpretation of the scene, providing
 
 From the paper:
 
->**Pilot** We run a pilot study with the double goal of collecting feedback and defining the task instructions.
+>**Pilot:** We run a pilot study with the double goal of collecting feedback and defining the task instructions.
 >With the results from the pilot we design a beta version of the task and we run a small batch of cases on the crowd-sourcing platform.
 >We manually inspect the results and we further refine the instructions and the formulation of the task before finally proceeding with the
 >annotation in bulk. The final annotation form is shown in Appendix D.
 
->***Procedure*** The participants are shown an image and three questions regarding three aspects or axes: _scene_, _actions_ and _rationales_
+>***Procedure:*** The participants are shown an image and three questions regarding three aspects or axes: _scene_, _actions_ and _rationales_
 > i,e. _Where is the picture taken?_, _What is the subject doing?_, _Why is the subject doing it?_. We explicitly ask the participants to use
 >their personal interpretation of the scene and add examples and suggestions in the instructions to further guide the annotators. Moreover,
 >differently from other VQA datasets like (Antol et al., 2015) and (Zhu et al., 2016), where each question can refer to different entities