diff --git a/R/poster.Rmd b/R/poster.Rmd
index 9ff9497..f75e2bf 100644
--- a/R/poster.Rmd
+++ b/R/poster.Rmd
@@ -147,37 +147,13 @@
     legend.text = element_text(size = rel(1))) 
 ```
 
-### Part-of-Speech proportions
 
-```{r pos_proportions, fig.width=14, fig.height=10, out.width = "100%"}
-POS_tag <- c(
-  "ADJ", 	"ADP",#	"PUNCT",
-  "ADV",	"AUX",	# "SYM",
-  # "INTJ",
-  "CCONJ", #	"X",
-  "NOUN",	"DET",
-  "PROPN",	#"NUM",
-  "VERB",	#"PART",
-  "PRON",
-  "SCONJ"
-  )
+# Pilot study
 
-icc_by_pos_tag <- icc %>% expand_grid(POS = POS_tag) %>%
-  rowwise() %>%
-  mutate(f = frequencyQuery(icc_con(lang), sprintf("[ud/p=%s]", POS))$f)
+* Identification of Light Verb Constructions with *take*
+* in order to investigate the limitations imposed by the very small corpus sizes
+* using RKorapClient [@kupietz_rkorapclient_2020] to access corpora and get reproducible results of the collocation analysis
 
-icc_by_pos_tag %>% ggplot(aes(x=lang, fill = POS, y=f)) +
-  geom_col() + scale_y_continuous(labels = label_number(scale_cut = cut_short_scale())) +
-  scale_fill_ids() + scale_color_ids() +
-  theme_ids(base_size=24) + 
-    theme(
-    axis.title.x = element_text(size = rel(1.5), face = "bold"),
-    axis.title.y = element_text(size = rel(1.5), face = "bold"),
-     axis.text = element_text(size = rel(1)),
-    legend.title = element_text(size = rel(1), face = "bold"),
-    legend.text = element_text(size = rel(1))) +
-  geom_text(aes(label=sprintf("%.2f%%", 100*f), y=f), position= position_stack(reverse = F, vjust = 0.5), color="black", size=6.2, family="Fira Sans Condensed")
-```
 
 # Identification of Light Verb Constructions with *take*
 
