diff --git a/l4/TM-Lab4.ipynb b/l4/TM-Lab4.ipynb
index 62b4f9c3fb7de1d27944e9f2ca810127b4ae0dea..c61c93da047e53532886a88272d91e08d0dc6c0f 100644
--- a/l4/TM-Lab4.ipynb
+++ b/l4/TM-Lab4.ipynb
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 190,
+   "execution_count": 50,
    "metadata": {
     "deletable": false,
     "editable": false,
@@ -87,7 +87,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 191,
+   "execution_count": 51,
    "metadata": {
     "deletable": false,
     "editable": false,
@@ -120,7 +120,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 192,
+   "execution_count": 52,
    "metadata": {},
    "outputs": [
     {
@@ -200,7 +200,7 @@
        "4                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         i loved these movies , and i cant wiat for the third one ! very funny , not suitable for chilren  "
       ]
      },
-     "execution_count": 192,
+     "execution_count": 52,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -239,7 +239,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 193,
+   "execution_count": 53,
    "metadata": {
     "deletable": false,
     "nbgrader": {
@@ -259,6 +259,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
+      "<Compressed Sparse Row sparse matrix of dtype 'float64'\n",
+      "\twith 579847 stored elements and shape (11914, 46619)>\n",
+      "  Coords\tValues\n",
       "  (0, 5852)\t0.06504921495797875\n",
       "  (0, 2193)\t0.1471548307342515\n",
       "  (0, 24915)\t0.09109607037535733\n",
@@ -334,7 +337,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 194,
+   "execution_count": 54,
    "metadata": {
     "deletable": false,
     "nbgrader": {
@@ -379,7 +382,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 195,
+   "execution_count": 55,
    "metadata": {
     "deletable": false,
     "nbgrader": {
@@ -424,12 +427,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 196,
+   "execution_count": 56,
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -459,7 +462,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 197,
+   "execution_count": 57,
    "metadata": {
     "deletable": false,
     "nbgrader": {
@@ -518,7 +521,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 198,
+   "execution_count": 58,
    "metadata": {
     "tags": [
      "solution"
@@ -529,9 +532,9 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Cluster 0: movie, cd, like, album, great, just, good, music, film, songs\n",
-      "Cluster 1: camera, product, use, lens, software, pictures, great, easy, does, used\n",
-      "Cluster 2: book, read, books, author, reading, story, like, quot, just, good\n"
+      "Cluster 0: product, use, software, does, great, program, used, just, work, good\n",
+      "Cluster 1: book, movie, album, like, cd, just, music, quot, great, film\n",
+      "Cluster 2: camera, lens, pictures, canon, digital, use, flash, battery, quality, great\n"
      ]
     }
    ],
@@ -580,7 +583,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 205,
+   "execution_count": 59,
    "metadata": {
     "deletable": false,
     "nbgrader": {
@@ -601,7 +604,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -665,7 +668,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 200,
+   "execution_count": 68,
    "metadata": {},
    "outputs": [
     {
@@ -719,23 +722,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 201,
+   "execution_count": 69,
    "metadata": {},
-   "outputs": [
-    {
-     "ename": "OSError",
-     "evalue": "[E050] Can't find model 'en_core_web_sm'. It doesn't seem to be a Python package or a valid path to a data directory.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mOSError\u001b[0m                                   Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[201], line 2\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mspacy\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m nlp \u001b[39m=\u001b[39m spacy\u001b[39m.\u001b[39;49mload(\u001b[39m\"\u001b[39;49m\u001b[39men_core_web_sm\u001b[39;49m\u001b[39m\"\u001b[39;49m)\n",
-      "File \u001b[0;32m~/projects/text-mining/l4/.venv/lib/python3.10/site-packages/spacy/__init__.py:51\u001b[0m, in \u001b[0;36mload\u001b[0;34m(name, vocab, disable, enable, exclude, config)\u001b[0m\n\u001b[1;32m     27\u001b[0m \u001b[39mdef\u001b[39;00m \u001b[39mload\u001b[39m(\n\u001b[1;32m     28\u001b[0m     name: Union[\u001b[39mstr\u001b[39m, Path],\n\u001b[1;32m     29\u001b[0m     \u001b[39m*\u001b[39m,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     34\u001b[0m     config: Union[Dict[\u001b[39mstr\u001b[39m, Any], Config] \u001b[39m=\u001b[39m util\u001b[39m.\u001b[39mSimpleFrozenDict(),\n\u001b[1;32m     35\u001b[0m ) \u001b[39m-\u001b[39m\u001b[39m>\u001b[39m Language:\n\u001b[1;32m     36\u001b[0m \u001b[39m    \u001b[39m\u001b[39m\"\"\"Load a spaCy model from an installed package or a local path.\u001b[39;00m\n\u001b[1;32m     37\u001b[0m \n\u001b[1;32m     38\u001b[0m \u001b[39m    name (str): Package name or model path.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     49\u001b[0m \u001b[39m    RETURNS (Language): The loaded nlp object.\u001b[39;00m\n\u001b[1;32m     50\u001b[0m \u001b[39m    \"\"\"\u001b[39;00m\n\u001b[0;32m---> 51\u001b[0m     \u001b[39mreturn\u001b[39;00m util\u001b[39m.\u001b[39;49mload_model(\n\u001b[1;32m     52\u001b[0m         name,\n\u001b[1;32m     53\u001b[0m         vocab\u001b[39m=\u001b[39;49mvocab,\n\u001b[1;32m     54\u001b[0m         disable\u001b[39m=\u001b[39;49mdisable,\n\u001b[1;32m     55\u001b[0m         enable\u001b[39m=\u001b[39;49menable,\n\u001b[1;32m     56\u001b[0m         exclude\u001b[39m=\u001b[39;49mexclude,\n\u001b[1;32m     57\u001b[0m         config\u001b[39m=\u001b[39;49mconfig,\n\u001b[1;32m     58\u001b[0m     )\n",
-      "File \u001b[0;32m~/projects/text-mining/l4/.venv/lib/python3.10/site-packages/spacy/util.py:472\u001b[0m, in \u001b[0;36mload_model\u001b[0;34m(name, vocab, disable, enable, exclude, config)\u001b[0m\n\u001b[1;32m    470\u001b[0m \u001b[39mif\u001b[39;00m name \u001b[39min\u001b[39;00m OLD_MODEL_SHORTCUTS:\n\u001b[1;32m    471\u001b[0m     \u001b[39mraise\u001b[39;00m \u001b[39mIOError\u001b[39;00m(Errors\u001b[39m.\u001b[39mE941\u001b[39m.\u001b[39mformat(name\u001b[39m=\u001b[39mname, full\u001b[39m=\u001b[39mOLD_MODEL_SHORTCUTS[name]))  \u001b[39m# type: ignore[index]\u001b[39;00m\n\u001b[0;32m--> 472\u001b[0m \u001b[39mraise\u001b[39;00m \u001b[39mIOError\u001b[39;00m(Errors\u001b[39m.\u001b[39mE050\u001b[39m.\u001b[39mformat(name\u001b[39m=\u001b[39mname))\n",
-      "\u001b[0;31mOSError\u001b[0m: [E050] Can't find model 'en_core_web_sm'. It doesn't seem to be a Python package or a valid path to a data directory."
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import spacy\n",
     "nlp = spacy.load(\"en_core_web_sm\")"
@@ -743,7 +732,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 73,
    "metadata": {
     "deletable": false,
     "nbgrader": {
@@ -770,8 +759,21 @@
     "        Each item in the list should be a list of tokens in the given\n",
     "        document, after preprocessing.\n",
     "    \"\"\"\n",
-    "    # YOUR CODE HERE\n",
-    "    raise NotImplementedError()"
+    "    new_source = []\n",
+    "\n",
+    "    with open('sotu_1975_2000.txt') as source:\n",
+    "        for line in source:\n",
+    "            doc = nlp(line)\n",
+    "\n",
+    "            sentence = []\n",
+    "\n",
+    "            for token in doc:\n",
+    "                if not token.is_stop and not token.is_alpha and len(token.text) >= 3:\n",
+    "                    sentence.append(token.text)\n",
+    "            \n",
+    "            new_source.append(sentence)\n",
+    "    \n",
+    "    return new_source"
    ]
   },
   {
@@ -785,7 +787,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 74,
    "metadata": {
     "deletable": false,
     "editable": false,
@@ -801,7 +803,19 @@
      "task": false
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "TypeError",
+     "evalue": "sequence item 0: expected str instance, spacy.tokens.token.Token found",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[74], line 3\u001b[0m\n\u001b[1;32m      1\u001b[0m documents \u001b[38;5;241m=\u001b[39m load_and_preprocess_documents()\n\u001b[0;32m----> 3\u001b[0m \u001b[38;5;28mprint\u001b[39m(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mDocument 42 after preprocessing: \u001b[39m\u001b[38;5;132;01m{\u001b[39;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m \u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mjoin\u001b[49m\u001b[43m(\u001b[49m\u001b[43mdocuments\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m42\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m)\u001b[49m\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m      4\u001b[0m \u001b[38;5;28;01massert\u001b[39;00m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m \u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;241m.\u001b[39mjoin(documents[\u001b[38;5;241m42\u001b[39m]) \u001b[38;5;241m==\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mreduce oil imports million barrels day end year million barrels day end\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m      5\u001b[0m success()\n",
+      "\u001b[0;31mTypeError\u001b[0m: sequence item 0: expected str instance, spacy.tokens.token.Token found"
+     ]
+    }
+   ],
    "source": [
     "documents = load_and_preprocess_documents()\n",
     "\n",