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diff --git a/notebooks/disease_retrieval_accuracy.ipynb b/notebooks/disease_retrieval_accuracy.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "945c420e-bb44-4ffb-b899-e049caf0d918",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "os.chdir('..')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "f2bdefb3-3e59-409a-81b4-2e9ffbdfdb1a",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/root/anaconda3/envs/kg_rag_test_2/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "from kg_rag.utility import *\n",
+    "from tqdm import tqdm\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "19fc98b9-64a8-40c0-9e5a-92b4392e6969",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "data = pd.read_csv('data/dataset_for_entity_retrieval_accuracy_analysis.csv')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "2851be4c-2a76-4f6d-b5f4-118e8122b155",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "VECTOR_DB_PATH = config_data[\"VECTOR_DB_PATH\"]\n",
+    "SENTENCE_EMBEDDING_MODEL_FOR_NODE_RETRIEVAL = config_data[\"SENTENCE_EMBEDDING_MODEL_FOR_NODE_RETRIEVAL\"]\n",
+    "\n",
+    "vectorstore = load_chroma(VECTOR_DB_PATH, SENTENCE_EMBEDDING_MODEL_FOR_NODE_RETRIEVAL)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "7255fbab-d8b4-43a3-b870-9d67ad79d061",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "322it [00:05, 56.20it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "CPU times: user 4.74 s, sys: 896 ms, total: 5.64 s\n",
+      "Wall time: 5.73 s\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "%%time\n",
+    "\n",
+    "correct_retrieval = 0\n",
+    "\n",
+    "for index, row in tqdm(data.iterrows()):\n",
+    "    question = row['text']\n",
+    "    entities = disease_entity_extractor_v2(question)  \n",
+    "    for entity in entities:\n",
+    "        node_search_result = vectorstore.similarity_search_with_score(entity, k=1)\n",
+    "        if node_search_result[0][0].page_content == row['node_hits']:\n",
+    "            correct_retrieval += 1 \n",
+    "            break\n",
+    "            \n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "2f997335-bff7-431c-bbd8-608513eddcc7",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Retrieval accuracy is 99.7%\n"
+     ]
+    }
+   ],
+   "source": [
+    "retrieval_accuracy = 100*correct_retrieval/data.shape[0]\n",
+    "print(f'Retrieval accuracy is {round(retrieval_accuracy,1)}%')\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "afe971ab-b8b9-4c88-9657-c588813b412f",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3 (ipykernel)",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}