diff --git a/main.ipynb b/main.ipynb
index b07eef2..dfa1a6f 100644
--- a/main.ipynb
+++ b/main.ipynb
@@ -24,17 +24,14 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 26,
    "metadata": {
     "tags": []
    },
    "outputs": [],
    "source": [
     "import pandas as pd\n",
-    "columns = ['FileId','Paper', 'Idk1', 'Year','Idk2','Idk3', 'LeftContext', 'RightContext']\n",
     "\n",
-    "# dev_data = pd.read_csv('dev-0/in.tsv', sep='\\t', names=columns, engine='python', quotechar='\"', error_bad_lines=False)\n",
-    "# dev_expected = pd.read_csv('dev-0/expected.tsv', sep='\\t', engine='python', quotechar='\"', error_bad_lines=False)\n",
     "dev_data = list()\n",
     "directory = 'dev-0'\n",
     "data_path = directory+'/in.tsv'\n",
@@ -53,7 +50,32 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def interpolate(bigram, unigramCounts, bigramCounts, listOfProb):\n",
+    "    lambdaValue = 0.4\n",
+    "    word1 = bigram[0]\n",
+    "    word2 = bigram[1]\n",
+    "    listOfProb[bigram] = (bigramCounts.get(bigram, 0))/(unigramCounts.get(word1, 0)) + (1-lambdaValue)*(unigramCounts.get(word2, 0))/(unigramCounts.get(word1, 0))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def calcProbability(bigram, unigramCounts, bigramCounts, listOfProb):\n",
+    "    word1 = bigram[0]\n",
+    "    word2 = bigram[1]\n",
+    "    listOfProb[bigram] = (bigramCounts.get(bigram, 0))/(unigramCounts.get(word1, 0))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -86,15 +108,13 @@
     "def calcBigramProb(listOfBigrams, unigramCounts, bigramCounts):\n",
     "    listOfProb = {}\n",
     "    for bigram in listOfBigrams:\n",
-    "        word1 = bigram[0]\n",
-    "        word2 = bigram[1]\n",
-    "        listOfProb[bigram] = (bigramCounts.get(bigram))/(sum(unigramCounts.values()))\n",
+    "        calcProbability(bigram, unigramCounts, bigramCounts, listOfProb)\n",
     "    return listOfProb"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 30,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -103,7 +123,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -112,7 +132,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 51,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -135,7 +155,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 52,
+   "execution_count": 33,
    "metadata": {
     "tags": []
    },