diff --git a/lab/lab_01.ipynb b/lab/lab_01.ipynb
index 0ffe833..055ca14 100644
--- a/lab/lab_01.ipynb
+++ b/lab/lab_01.ipynb
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 191,
    "id": "narrow-romantic",
    "metadata": {},
    "outputs": [],
@@ -71,7 +71,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 192,
    "id": "indonesian-electron",
    "metadata": {},
    "outputs": [],
@@ -82,7 +82,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 193,
    "id": "compact-trinidad",
    "metadata": {},
    "outputs": [
@@ -92,7 +92,7 @@
        "['Press the ENTER button']"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 193,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -119,7 +119,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 194,
    "id": "exposed-daniel",
    "metadata": {},
    "outputs": [],
@@ -139,7 +139,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 195,
    "id": "serial-velvet",
    "metadata": {},
    "outputs": [
@@ -149,7 +149,7 @@
        "['Press the ENTER button', 'Press the ENTER key']"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 195,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -176,7 +176,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 196,
    "id": "every-gibson",
    "metadata": {},
    "outputs": [
@@ -186,7 +186,7 @@
        "[]"
       ]
      },
-     "execution_count": 6,
+     "execution_count": 196,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -213,13 +213,37 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 197,
    "id": "protected-rings",
    "metadata": {},
    "outputs": [],
    "source": [
+    "def preprocess(sentence):\n",
+    "    return sentence.lower()\n",
+    "\n",
     "def tm_lookup(sentence):\n",
-    "    return ''"
+    "    return [entry[1] for entry in translation_memory if preprocess(entry[0]) == preprocess(sentence)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 198,
+   "id": "7baee10b",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Press the ENTER button', 'Press the ENTER key']"
+      ]
+     },
+     "execution_count": 198,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tm_lookup('Wciśnij przycisk ENTER')"
    ]
   },
   {
@@ -232,17 +256,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 199,
    "id": "severe-alloy",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "''"
+       "[]"
       ]
      },
-     "execution_count": 18,
+     "execution_count": 199,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -261,13 +285,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 200,
    "id": "structural-diesel",
    "metadata": {},
    "outputs": [],
    "source": [
+    "import string\n",
+    "\n",
+    "def preprocess(s):\n",
+    "    translator = str.maketrans('', '', string.punctuation)\n",
+    "    return s.translate(translator).lower()\n",
+    "\n",
     "def tm_lookup(sentence):\n",
-    "    return ''"
+    "    return [entry[1] for entry in translation_memory if preprocess(entry[0]) == preprocess(sentence)]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 201,
+   "id": "c03c6709",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['Press the ENTER button', 'Press the ENTER key']"
+      ]
+     },
+     "execution_count": 201,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tm_lookup('Wciśnij przycisk [ENTER]')"
    ]
   },
   {
@@ -280,17 +331,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 202,
    "id": "brief-senegal",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "''"
+       "[]"
       ]
      },
-     "execution_count": 12,
+     "execution_count": 202,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -317,13 +368,43 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 203,
    "id": "mathematical-customs",
    "metadata": {},
    "outputs": [],
    "source": [
+    "def compare_sentences(l1, l2):\n",
+    "    return sum([1 for i, j in zip(l1.split(), l2.split()) if i != j]) <= 1\n",
+    "\n",
+    "import string\n",
+    "\n",
+    "def preprocess(s):\n",
+    "    translator = str.maketrans('', '', string.punctuation)\n",
+    "    return s.translate(translator).lower()\n",
+    "\n",
     "def tm_lookup(sentence):\n",
-    "    return ''"
+    "    return [entry[1] for entry in translation_memory if compare_sentences(preprocess(entry[0]), preprocess(sentence))]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 204,
+   "id": "6264b722",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['System restart required']"
+      ]
+     },
+     "execution_count": 204,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "tm_lookup('Wymagane ponowne uruchomienie maszyny')"
    ]
   },
   {
@@ -344,7 +425,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 205,
    "id": "humanitarian-wrong",
    "metadata": {},
    "outputs": [],
@@ -362,7 +443,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 206,
    "id": "located-perception",
    "metadata": {},
    "outputs": [],
@@ -374,7 +455,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 207,
    "id": "advised-casting",
    "metadata": {},
    "outputs": [
@@ -384,7 +465,7 @@
        "[('przycisk', 'button'), ('drukarka', 'printer')]"
       ]
      },
-     "execution_count": 17,
+     "execution_count": 207,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -406,7 +487,7 @@
    "id": "defensive-fifteen",
    "metadata": {},
    "source": [
-    "Odpowiedź:"
+    "Odpowiedź: Jeżeli implementacja wygląda tak jak powyżej, złożoność to `O(n*m)`, ponieważ dla każdego słowa iteracyjnie przechodzimy przez cały nasz słownik i szukamy odpowiednika"
    ]
   },
   {
@@ -419,13 +500,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 19,
+   "execution_count": 208,
+   "id": "aca5d340",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('przycisk', 'button')]"
+      ]
+     },
+     "execution_count": 208,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "glossary_lookup('Każda Drukarka posiada przycisk wznowienia drukowania')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 209,
    "id": "original-tunisia",
    "metadata": {},
    "outputs": [],
    "source": [
     "def glossary_lookup(sentence):\n",
-    "    return ''"
+    "    sentence_words = [word.lower() for word in sentence.split()]\n",
+    "    return [entry for entry in glossary if entry[0] in sentence_words]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 210,
+   "id": "716bbbe9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('przycisk', 'button'), ('drukarka', 'printer')]"
+      ]
+     },
+     "execution_count": 210,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "glossary_lookup('Każda drukarka posiada przycisk wznowienia drukowania')"
    ]
   },
   {
@@ -438,13 +562,50 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 20,
+   "execution_count": 211,
+   "id": "32dec661",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "glossary = [('komputer', 'computer'), ('przycisk', 'button'), ('drukarka', 'printer')]\n",
+    "glossary = {\n",
+    "    'komputer': 'computer',\n",
+    "    'przycisk': 'button',\n",
+    "    'drukarka': 'printer'\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 212,
    "id": "adolescent-semiconductor",
    "metadata": {},
    "outputs": [],
    "source": [
     "def glossary_lookup(sentence):\n",
-    "    return ''"
+    "    sentence_words = [word.lower() for word in sentence.split() if word.lower() in glossary]\n",
+    "    return [(word, glossary[word]) for word in sentence_words]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 213,
+   "id": "d1e991c6",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[('drukarka', 'printer'), ('przycisk', 'button')]"
+      ]
+     },
+     "execution_count": 213,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "glossary_lookup('Każda drukarka posiada przycisk wznowienia drukowania')"
    ]
   }
  ],
@@ -467,7 +628,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.14"
   },
   "subtitle": "1. Podstawowe techniki wspomagania tłumaczenia",
   "title": "Komputerowe wspomaganie tłumaczenia",
diff --git a/lab/lab_02.ipynb b/lab/lab_02.ipynb
index 10c2003..9cf061b 100644
--- a/lab/lab_02.ipynb
+++ b/lab/lab_02.ipynb
@@ -57,7 +57,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 17,
    "id": "confident-prison",
    "metadata": {},
    "outputs": [],
@@ -80,13 +80,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 18,
    "id": "continental-submission",
    "metadata": {},
    "outputs": [],
    "source": [
     "def ice_lookup(sentence, prev_sentence, next_sentence):\n",
-    "    return []"
+    "    # Wyniki dopasowania ICE\n",
+    "    ice_matches = []\n",
+    "\n",
+    "    # Iterujemy przez pamięć tłumaczeń, pomijając pierwszy i ostatni element dla bezpieczeństwa kontekstowego\n",
+    "    for index in range(1, len(translation_memory) - 1):\n",
+    "        # Pobieramy obecne, poprzednie i następne zdania z TM\n",
+    "        prev_tm_sentence, _ = translation_memory[index - 1]\n",
+    "        current_tm_sentence, current_tm_translation = translation_memory[index]\n",
+    "        next_tm_sentence, _ = translation_memory[index + 1]\n",
+    "\n",
+    "        # Sprawdzamy, czy wszystkie trzy zdania zgadzają się z odpowiednikami w TM\n",
+    "        if (prev_tm_sentence == prev_sentence and current_tm_sentence == current_sentence  and next_tm_sentence == next_sentence):\n",
+    "            ice_matches.append(current_tm_translation)\n",
+    "\n",
+    "    return ice_matches"
    ]
   },
   {
@@ -119,7 +133,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 19,
    "id": "fourth-pillow",
    "metadata": {},
    "outputs": [],
@@ -141,7 +155,11 @@
    "id": "graduate-theorem",
    "metadata": {},
    "source": [
-    "Odpowiedź:"
+    "Odpowiedź: Nie, ponieważ w tej funkcji interesuje nas tylko długość zdania, tzn. drugi warunek nie będzie spełniony\n",
+    "\n",
+    "Przykład: `kot != bok`, a dla tej funkcji zwróci 0\n",
+    "\n",
+    "Spełnione warunki: 1, 3, 4"
    ]
   },
   {
@@ -154,7 +172,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 20,
    "id": "continued-christopher",
    "metadata": {},
    "outputs": [],
@@ -179,7 +197,40 @@
    "id": "metallic-leave",
    "metadata": {},
    "source": [
-    "Odpowiedź:"
+    "Odpowiedź: Tak, spełnia wszystkie warunki\n",
+    "\n",
+    "Sprawdzenie dla warunku 4"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "349a3547",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "True\n",
+      "True\n",
+      "True\n",
+      "True\n"
+     ]
+    }
+   ],
+   "source": [
+    "# x == y i y == z\n",
+    "print(sentence_distance(\"kot\", \"kot\") + sentence_distance(\"kot\", \"kot\") >= sentence_distance(\"kot\", \"kot\"))\n",
+    "\n",
+    "# x == y i y != z\n",
+    "print(sentence_distance(\"kot\", \"kot\") + sentence_distance(\"kot\", \"pies\") >= sentence_distance(\"kot\", \"pies\"))\n",
+    "\n",
+    "# x != y i y == z\n",
+    "print(sentence_distance(\"kot\", \"pies\") + sentence_distance(\"pies\", \"pies\") >= sentence_distance(\"kot\", \"pies\"))\n",
+    "\n",
+    "# x != y i y != z\n",
+    "print(sentence_distance(\"kot\", \"pies\") + sentence_distance(\"pies\", \"kot\") >= sentence_distance(\"kot\", \"kot\"))"
    ]
   },
   {
@@ -206,7 +257,11 @@
    "id": "bibliographic-stopping",
    "metadata": {},
    "source": [
-    "Odpowiedź:"
+    "Odpowiedź:\n",
+    "- Dystans Levenshteina jest zawsze nieujemny\n",
+    "- Jeśli dwa ciągi są identyczne, nie potrzeba żadnych operacji do przekształcenia jednego w drugi\n",
+    "- Dystans Levenshteina jest symetryczny, ponieważ liczba operacji wymaganych do przekształcenia ciągu A w ciąg B jest taka sama jak liczba operacji potrzebnych do przekształcenia ciągu B w ciąg A\n",
+    "- Dystans Levenshteina spełnia nierówność trójkąta. Można to uzasadnić rozważając, że przekształcenie ciągu X w Y przez ciąg pośredni Z (najpierw przekształcając X w Z, a następnie Z w Y) nie będzie wymagać więcej operacji niż bezpośrednie przekształcenie X w Y"
    ]
   },
   {
@@ -223,7 +278,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 21,
    "id": "secondary-wrist",
    "metadata": {},
    "outputs": [
@@ -233,7 +288,7 @@
        "2"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 21,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -254,7 +309,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 22,
    "id": "associate-tuner",
    "metadata": {},
    "outputs": [],
@@ -273,7 +328,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 23,
    "id": "focal-pathology",
    "metadata": {},
    "outputs": [
@@ -283,7 +338,7 @@
        "0.9166666666666666"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 23,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -294,7 +349,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 24,
    "id": "roman-ceiling",
    "metadata": {},
    "outputs": [
@@ -304,7 +359,7 @@
        "0.9428571428571428"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 24,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -315,7 +370,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 25,
    "id": "invisible-cambodia",
    "metadata": {},
    "outputs": [
@@ -325,7 +380,7 @@
        "0.631578947368421"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 25,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -344,13 +399,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 26,
    "id": "genetic-cradle",
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Write a fuzzy_lookup function that will search the translation memory for all sentences whose Levenshtein similarity to the searched sentence is greater than or equal to a set threshold.\n",
     "def fuzzy_lookup(sentence, threshold):\n",
-    "    return []"
+    "    fuzzy_matches = []\n",
+    "\n",
+    "    # Iterujemy przez pamięć tłumaczeń\n",
+    "    for tm_sentence, tm_translation in translation_memory:\n",
+    "        # Sprawdzamy, czy podobieństwo Levenshteina jest większe niż próg\n",
+    "        if levenshtein_similarity(sentence, tm_sentence) >= threshold:\n",
+    "            fuzzy_matches.append(tm_translation)\n",
+    "\n",
+    "    return fuzzy_matches"
    ]
   }
  ],
@@ -373,7 +437,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.14"
   },
   "subtitle": "2. Zaawansowane użycie pamięci tłumaczeń",
   "title": "Komputerowe wspomaganie tłumaczenia",
diff --git a/lab/lab_03.ipynb b/lab/lab_03.ipynb
index 5707f0d..f9ba649 100644
--- a/lab/lab_03.ipynb
+++ b/lab/lab_03.ipynb
@@ -63,7 +63,7 @@
    "id": "diverse-sunglasses",
    "metadata": {},
    "source": [
-    "Odpowiedź:"
+    "Odpowiedź: Wynik z Google Translate to `metal cabinet guides`"
    ]
   },
   {
@@ -86,12 +86,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 11,
    "id": "loving-prince",
    "metadata": {},
    "outputs": [],
    "source": [
-    "text = \" For all Java programmers:\"\n",
+    "text =  \" For all Java programmers:\"\n",
     "text += \" This section explains how to compile and run a Swing application from the command line.\"\n",
     "text += \" For information on compiling and running a Swing application using NetBeans IDE,\"\n",
     "text += \" see Running Tutorial Examples in NetBeans IDE. The compilation instructions work for all Swing programs\"\n",
@@ -110,7 +110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 12,
    "id": "bound-auction",
    "metadata": {},
    "outputs": [],
@@ -128,13 +128,46 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 13,
    "id": "cognitive-cedar",
    "metadata": {},
    "outputs": [],
    "source": [
     "def terminology_lookup():\n",
-    "    return []"
+    "    for term in dictionary:\n",
+    "        start = 0\n",
+    "        while True:\n",
+    "            start = text.find(term, start)\n",
+    "            if start == -1:\n",
+    "                break\n",
+    "            end = start + len(term)\n",
+    "            print(f'{term}: ({start}, {end})')\n",
+    "            start = end"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "0a4a26ba",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "program: (14, 21)\n",
+      "program: (291, 298)\n",
+      "program: (468, 475)\n",
+      "program: (516, 523)\n",
+      "program: (533, 540)\n",
+      "application: (80, 91)\n",
+      "application: (164, 175)\n",
+      "application: (322, 333)\n"
+     ]
+    }
+   ],
+   "source": [
+    "terminology_lookup()"
    ]
   },
   {
@@ -161,7 +194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 15,
    "id": "tribal-attention",
    "metadata": {},
    "outputs": [
@@ -169,108 +202,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      " \n",
-      "for\n",
-      "all\n",
-      "Java\n",
-      "programmer\n",
-      ":\n",
-      "this\n",
-      "section\n",
-      "explain\n",
-      "how\n",
-      "to\n",
-      "compile\n",
-      "and\n",
-      "run\n",
-      "a\n",
-      "swing\n",
-      "application\n",
-      "from\n",
-      "the\n",
-      "command\n",
-      "line\n",
-      ".\n",
-      "for\n",
-      "information\n",
-      "on\n",
-      "compile\n",
-      "and\n",
-      "run\n",
-      "a\n",
-      "swing\n",
-      "application\n",
-      "use\n",
-      "NetBeans\n",
-      "IDE\n",
-      ",\n",
-      "see\n",
-      "Running\n",
-      "Tutorial\n",
-      "Examples\n",
-      "in\n",
-      "NetBeans\n",
-      "IDE\n",
-      ".\n",
-      "the\n",
-      "compilation\n",
-      "instruction\n",
-      "work\n",
-      "for\n",
-      "all\n",
-      "swing\n",
-      "program\n",
-      "—\n",
-      "applet\n",
-      ",\n",
-      "as\n",
-      "well\n",
-      "as\n",
-      "application\n",
-      ".\n",
-      "here\n",
-      "be\n",
-      "the\n",
-      "step\n",
-      "-PRON-\n",
-      "need\n",
-      "to\n",
-      "follow\n",
-      ":\n",
-      "install\n",
-      "the\n",
-      "late\n",
-      "release\n",
-      "of\n",
-      "the\n",
-      "Java\n",
-      "SE\n",
-      "platform\n",
-      ",\n",
-      "if\n",
-      "-PRON-\n",
-      "have\n",
-      "not\n",
-      "already\n",
-      "do\n",
-      "so\n",
-      ".\n",
-      "create\n",
-      "a\n",
-      "program\n",
-      "that\n",
-      "use\n",
-      "Swing\n",
-      "component\n",
-      ".\n",
-      "compile\n",
-      "the\n",
-      "program\n",
-      ".\n",
-      "run\n",
-      "the\n",
-      "program\n",
-      ".\n"
+      "  for all Java programmer : this section explain how to compile and run a swing application from the command line . for information on compile and run a swing application use NetBeans IDE , see run Tutorial Examples in NetBeans IDE . the compilation instruction work for all Swing program — applet , as well as application . here be the step you need to follow : install the late release of the Java SE platform , if you have not already do so . create a program that use swing component . compile the program . run the program . "
      ]
     }
    ],
@@ -281,7 +213,7 @@
     "doc = nlp(text)\n",
     "\n",
     "for token in doc:\n",
-    "    print(token.lemma_)"
+    "    print(token.lemma_, end=' ')"
    ]
   },
   {
@@ -302,13 +234,40 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 40,
    "id": "surgical-demonstration",
    "metadata": {},
    "outputs": [],
    "source": [
     "def terminology_lookup():\n",
-    "    return []"
+    "    for term in dictionary:\n",
+    "        for token in doc:\n",
+    "            if token.lemma_ == term:\n",
+    "                print(f'{token}: ({token.idx}, {token.idx + len(token)})')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "74f600ea",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "programs: (291, 299)\n",
+      "program: (468, 475)\n",
+      "program: (516, 523)\n",
+      "program: (533, 540)\n",
+      "application: (80, 91)\n",
+      "application: (164, 175)\n",
+      "applications: (322, 334)\n"
+     ]
+    }
+   ],
+   "source": [
+    "terminology_lookup()"
    ]
   },
   {
@@ -337,13 +296,56 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 22,
    "id": "superb-butterfly",
    "metadata": {},
    "outputs": [],
    "source": [
     "def get_nouns(text):\n",
-    "    return []"
+    "    doc = nlp(text)\n",
+    "    return [token.text for token in doc if token.pos_ == 'NOUN']"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "2bfedfa3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "['programmers',\n",
+       " 'section',\n",
+       " 'Swing',\n",
+       " 'application',\n",
+       " 'command',\n",
+       " 'line',\n",
+       " 'information',\n",
+       " 'Swing',\n",
+       " 'application',\n",
+       " 'compilation',\n",
+       " 'instructions',\n",
+       " 'programs',\n",
+       " 'applets',\n",
+       " 'applications',\n",
+       " 'steps',\n",
+       " 'release',\n",
+       " 'platform',\n",
+       " 'program',\n",
+       " 'Swing',\n",
+       " 'components',\n",
+       " 'program',\n",
+       " 'program']"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "get_nouns(text)"
    ]
   },
   {
@@ -356,7 +358,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 19,
    "id": "acting-tolerance",
    "metadata": {},
    "outputs": [],
@@ -374,13 +376,54 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 26,
    "id": "eight-redhead",
    "metadata": {},
    "outputs": [],
    "source": [
     "def extract_terms(text):\n",
-    "    return []"
+    "    doc = nlp(text)\n",
+    "    terms = {}\n",
+    "    for token in doc:\n",
+    "        if token.pos_ == 'NOUN':\n",
+    "            term = token.lemma_\n",
+    "            terms[term] = terms.get(term, 0) + 1\n",
+    "    return terms"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "07c1122a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "{'programmer': 1,\n",
+       " 'section': 1,\n",
+       " 'swing': 3,\n",
+       " 'application': 3,\n",
+       " 'command': 1,\n",
+       " 'line': 1,\n",
+       " 'information': 1,\n",
+       " 'compilation': 1,\n",
+       " 'instruction': 1,\n",
+       " 'program': 4,\n",
+       " 'applet': 1,\n",
+       " 'step': 1,\n",
+       " 'release': 1,\n",
+       " 'platform': 1,\n",
+       " 'component': 1}"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "extract_terms(text)"
    ]
   },
   {
@@ -393,14 +436,82 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 32,
    "id": "monetary-mambo",
    "metadata": {},
    "outputs": [],
    "source": [
+    "# Extract and count nouns, verbs and adjectives\n",
     "def extract_terms(text):\n",
-    "    return []"
+    "    doc = nlp(text)\n",
+    "    terms = {\"nouns\": {}, \"verbs\": {}, \"adjectives\": {}}\n",
+    "    for token in doc:\n",
+    "        if token.pos_ == 'NOUN':\n",
+    "            term = token.lemma_\n",
+    "            terms[\"nouns\"][term] = terms[\"nouns\"].get(term, 0) + 1\n",
+    "        elif token.pos_ == 'VERB':\n",
+    "            term = token.lemma_\n",
+    "            terms[\"verbs\"][term] = terms[\"verbs\"].get(term, 0) + 1\n",
+    "        elif token.pos_ == 'ADJ':\n",
+    "            term = token.lemma_\n",
+    "            terms[\"adjectives\"][term] = terms[\"adjectives\"].get(term, 0) + 1\n",
+    "\n",
+    "    return terms"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "1eb48136",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "{'adjectives': {'late': 1},\n",
+      " 'nouns': {'applet': 1,\n",
+      "           'application': 3,\n",
+      "           'command': 1,\n",
+      "           'compilation': 1,\n",
+      "           'component': 1,\n",
+      "           'information': 1,\n",
+      "           'instruction': 1,\n",
+      "           'line': 1,\n",
+      "           'platform': 1,\n",
+      "           'program': 4,\n",
+      "           'programmer': 1,\n",
+      "           'release': 1,\n",
+      "           'section': 1,\n",
+      "           'step': 1,\n",
+      "           'swing': 3},\n",
+      " 'verbs': {'compile': 3,\n",
+      "           'create': 1,\n",
+      "           'do': 1,\n",
+      "           'explain': 1,\n",
+      "           'follow': 1,\n",
+      "           'install': 1,\n",
+      "           'need': 1,\n",
+      "           'run': 4,\n",
+      "           'see': 1,\n",
+      "           'use': 2,\n",
+      "           'work': 1}}\n"
+     ]
+    }
+   ],
+   "source": [
+    "from pprint import pprint\n",
+    "\n",
+    "pprint(extract_terms(text))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "62aeea83",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {
@@ -422,7 +533,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.10.14"
   },
   "subtitle": "3. Terminologia",
   "title": "Komputerowe wspomaganie tłumaczenia",