diff --git a/skrypcik_v1.py b/skrypcik_v1.py
new file mode 100644
index 0000000..ebb243e
--- /dev/null
+++ b/skrypcik_v1.py
@@ -0,0 +1,57 @@
+import pandas as pd
+
+
+def correct_labels(input_file, output_file):
+    df = pd.read_csv(input_file, sep="\t", names=["Text"])
+
+    corrected_lines = []
+
+    for line in df["Text"]:
+        tokens = line.split(" ")
+        corrected_tokens = []
+        previous_token = "O"
+
+        for token in tokens:
+            if (
+                token == "I-ORG"
+                and previous_token != "B-ORG"
+                and previous_token != "I-ORG"
+            ):
+                corrected_tokens.append("B-ORG")
+            elif (
+                token == "I-PER"
+                and previous_token != "B-PER"
+                and previous_token != "I-PER"
+            ):
+                corrected_tokens.append("B-PER")
+            elif (
+                token == "I-LOC"
+                and previous_token != "B-LOC"
+                and previous_token != "I-LOC"
+            ):
+                corrected_tokens.append("B-LOC")
+            elif (
+                token == "I-MISC"
+                and previous_token != "B-MISC"
+                and previous_token != "I-MISC"
+            ):
+                corrected_tokens.append("B-MISC")
+            else:
+                corrected_tokens.append(token)
+
+            previous_token = token
+
+        corrected_line = " ".join(corrected_tokens)
+        corrected_lines.append(corrected_line)
+
+    df["Text"] = corrected_lines
+    df.to_csv(output_file, sep="\t", index=False, header=False)
+
+
+input_file = "dev-0/out.tsv"
+output_file = "dev-0/out_v1.tsv"
+correct_labels(input_file, output_file)
+
+input_file = "test-A/out.tsv"
+output_file = "test-A/out_v1.tsv"
+correct_labels(input_file, output_file)
\ No newline at end of file
diff --git a/skrypcik_v2.py b/skrypcik_v2.py
new file mode 100644
index 0000000..a9499da
--- /dev/null
+++ b/skrypcik_v2.py
@@ -0,0 +1,86 @@
+import pandas as pd
+
+
+def correct_labels(input_file, output_file):
+    df = pd.read_csv(input_file, sep="\t", names=["Text"])
+
+    corrected_lines = []
+
+    for line in df["Text"]:
+        tokens = line.split(" ")
+        corrected_tokens = []
+
+        previous_token = "O"
+        token = tokens[0]
+
+        for t in range(len(tokens)):
+            if t + 1 < len(tokens):
+                next_token = tokens[t + 1]
+            else:
+                next_token = "O"
+
+            if token == "I-ORG" and previous_token != "B-ORG" and previous_token != "I-ORG":
+                if next_token == "I-ORG":
+                    corrected_token = "B-ORG"
+                elif previous_token == "B-PER":
+                    corrected_token = "I-PER"
+                elif previous_token == "B-LOC":
+                    corrected_token = "I-LOC"
+                elif previous_token == "B-MISC":
+                    corrected_token = "I-MISC"
+                else:
+                    corrected_token = "B-ORG"
+            elif token == "I-PER" and previous_token != "B-PER" and previous_token != "I-PER":
+                if next_token == "I-PER":
+                    corrected_token = "B-PER"
+                elif previous_token == "B-ORG":
+                    corrected_token = "I-ORG"
+                elif previous_token == "B-LOC":
+                    corrected_token = "I-LOC"
+                elif previous_token == "B-MISC":
+                    corrected_token = "I-MISC"
+                else:
+                    corrected_token = "B-PER"
+            elif token == "I-LOC" and previous_token != "B-LOC" and previous_token != "I-LOC":
+                if next_token == "I-LOC":
+                    corrected_token = "B-LOC"
+                elif previous_token == "B-ORG":
+                    corrected_token = "I-ORG"
+                elif previous_token == "B-PER":
+                    corrected_token = "I-PER"
+                elif previous_token == "B-MISC":
+                    corrected_token = "I-MISC"
+                else:
+                    corrected_token = "B-LOC"
+            elif token == "I-MISC" and previous_token != "B-MISC" and previous_token != "I-MISC":
+                if next_token == "I-MISC":
+                    corrected_token = "B-MISC"
+                elif previous_token == "B-ORG":
+                    corrected_token = "I-ORG"
+                elif previous_token == "B-PER":
+                    corrected_token = "I-PER"
+                elif previous_token == "B-LOC":
+                    corrected_token = "I-LOC"
+                else:
+                    corrected_token = "B-MISC"
+            else:
+                corrected_token = token
+
+            corrected_tokens.append(corrected_token)
+            previous_token = corrected_token
+            token = next_token
+
+        corrected_line = " ".join(corrected_tokens)
+        corrected_lines.append(corrected_line)
+
+    df["Text"] = corrected_lines
+    df.to_csv(output_file, sep="\t", index=False, header=False)
+
+
+input_file = "dev-0/out.tsv"
+output_file = "dev-0/out_v2.tsv"
+correct_labels(input_file, output_file)
+
+input_file = "test-A/out.tsv"
+output_file = "test-A/out_v2.tsv"
+correct_labels(input_file, output_file)