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add tasks 1-3

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Krystian Osiński 2024-04-14 16:26:09 +02:00
parent 71ca3b66ed
commit 8c25ab8484
3 changed files with 702 additions and 82 deletions
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179
lab/lab_01.ipynb
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@ -52,7 +52,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 45,
"id": "narrow-romantic", "id": "narrow-romantic",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -71,7 +71,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 46,
"id": "indonesian-electron", "id": "indonesian-electron",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -82,7 +82,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 47,
"id": "compact-trinidad", "id": "compact-trinidad",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -92,7 +92,7 @@
"['Press the ENTER button']" "['Press the ENTER button']"
] ]
}, },
"execution_count": 3, "execution_count": 47,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -119,7 +119,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 48,
"id": "exposed-daniel", "id": "exposed-daniel",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -139,7 +139,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 49,
"id": "serial-velvet", "id": "serial-velvet",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -149,7 +149,7 @@
"['Press the ENTER button', 'Press the ENTER key']" "['Press the ENTER button', 'Press the ENTER key']"
] ]
}, },
"execution_count": 5, "execution_count": 49,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -176,17 +176,17 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 52,
"id": "every-gibson", "id": "every-gibson",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"[]" "['Press the ENTER button', 'Press the ENTER key']"
] ]
}, },
"execution_count": 6, "execution_count": 52,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -213,13 +213,13 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 51,
"id": "protected-rings", "id": "protected-rings",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"def tm_lookup(sentence):\n", "def tm_lookup(sentence):\n",
" return ''" " return [entry[1] for entry in translation_memory if entry[0].lower() == sentence.lower()]"
] ]
}, },
{ {
@ -232,17 +232,17 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 18, "execution_count": 55,
"id": "severe-alloy", "id": "severe-alloy",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"''" "['Press the ENTER button', 'Press the ENTER key']"
] ]
}, },
"execution_count": 18, "execution_count": 55,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -261,13 +261,21 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 11, "execution_count": 86,
"id": "structural-diesel", "id": "structural-diesel",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"import string\n",
"\n",
"def sentence_similar(sentence):\n",
" translator = str.maketrans('', '', string.punctuation)\n",
" return sentence.translate(translator)\n",
"\n",
"def tm_lookup(sentence):\n", "def tm_lookup(sentence):\n",
" return ''" " return [entry[1] for entry in translation_memory if entry[0].lower() == sentence_similar(sentence).lower()]\n",
"\n",
"#print(string.punctuation)"
] ]
}, },
{ {
@ -280,17 +288,17 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 12, "execution_count": 67,
"id": "brief-senegal", "id": "brief-senegal",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
{ {
"data": { "data": {
"text/plain": [ "text/plain": [
"''" "['System restart required']"
] ]
}, },
"execution_count": 12, "execution_count": 67,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -317,13 +325,30 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 14, "execution_count": 66,
"id": "mathematical-customs", "id": "mathematical-customs",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"def tm_lookup(sentence):\n", "def tm_lookup(sentence):\n",
" return ''" " inWords = sentence_similar(sentence).lower().split(\" \")\n",
" lenSentence = len(inWords)\n",
" matchWords = 0\n",
" answer = []\n",
" for entry in translation_memory:\n",
" dicWords = entry[0].lower().split(\" \")\n",
" \n",
" for i in range(lenSentence-1):\n",
" if inWords[i] == dicWords[i]:\n",
" matchWords += 1\n",
" \n",
" if matchWords >= lenSentence-1:\n",
" answer.append(entry[1])\n",
" matchWords = 0\n",
" else:\n",
" matchWords = 0\n",
"\n",
" return answer"
] ]
}, },
{ {
@ -344,7 +369,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 15, "execution_count": 68,
"id": "humanitarian-wrong", "id": "humanitarian-wrong",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -362,19 +387,29 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 16, "execution_count": 84,
"id": "located-perception", "id": "located-perception",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"def glossary_lookup(sentence):\n", "def glossary_lookup(sentence):\n",
" sentence_words = sentence.split()\n", " sentence_words = sentence.split()\n",
" return [entry for entry in glossary if entry[0] in sentence_words]" " return [entry for entry in glossary if entry[0] in sentence_words]\n",
"\n",
"def exercise4help(sentence):\n",
" sentence_words = sentence.split()\n",
" answer = []\n",
" for entry in glossary: #przechodzimy przez każdą tuple więc (n)\n",
" if entry[0] in sentence_words: # (m) porównań\n",
" answer.append(entry)\n",
" return answer\n",
"\n",
"#dla każdego hasła w słowniku, robimy tyle porównań ile jest słów w zdaniu O(n*m)"
] ]
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 17, "execution_count": 76,
"id": "advised-casting", "id": "advised-casting",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -384,13 +419,41 @@
"[('przycisk', 'button'), ('drukarka', 'printer')]" "[('przycisk', 'button'), ('drukarka', 'printer')]"
] ]
}, },
"execution_count": 17, "execution_count": 76,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
], ],
"source": [ "source": [
"glossary_lookup('Każda drukarka posiada przycisk wznowienia drukowania')" "glossary_lookup('Każda drukarka posiada przycisk wznowienia drukowania')\n"
]
},
{
"cell_type": "code",
"execution_count": 81,
"id": "70ae3dd8-d4ca-4a59-b8a9-ca47583bf54a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"3\n"
]
},
{
"data": {
"text/plain": [
"[('przycisk', 'button'), ('drukarka', 'printer')]"
]
},
"execution_count": 81,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"exercise4help('Każda drukarka posiada przycisk wznowienia drukowania')"
] ]
}, },
{ {
@ -406,7 +469,7 @@
"id": "defensive-fifteen", "id": "defensive-fifteen",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Odpowiedź:" "Odpowiedź: O(m*n)"
] ]
}, },
{ {
@ -419,13 +482,27 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 19, "execution_count": 82,
"id": "original-tunisia", "id": "original-tunisia",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"[('przycisk', 'button'), ('drukarka', 'printer')]"
]
},
"execution_count": 82,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"def glossary_lookup(sentence):\n", "def glossary_lookup(sentence):\n",
" return ''" " sentence_words = sentence.lower().split()\n",
" return [entry for entry in glossary if entry[0] in sentence_words]\n",
"\n",
"glossary_lookup('Każda DRUKARKA posiada PRZYCISK wznowienia drukowania')"
] ]
}, },
{ {
@ -438,13 +515,41 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 20, "execution_count": 108,
"id": "adolescent-semiconductor", "id": "adolescent-semiconductor",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"[('drukarka', 'printer'), ('drukarka', 'printer'), ('przycisk', 'button')]"
]
},
"execution_count": 109,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"glossary = {\n",
" 'komputer': 'computer',\n",
" 'przycisk': 'button', \n",
" 'drukarka': 'printer'\n",
"}\n",
"\n",
"#glossary.get('komputer') == None\n",
"\n",
"def glossary_lookup(sentence):\n", "def glossary_lookup(sentence):\n",
" return ''" " sentence_words = set(sentence.split()) #umieszczamy w zbiorze aby uniknąć przetwarzania mniejszej ilości słów.\n",
" answer = []\n",
" for word in sentence_words: # dla każdego słowa w zdaniu (m)\n",
" translated_word = glossary.get(word) #pobieramy zawartosć ze słownika \n",
" if translated_word != None: # (porównanie m razy)\n",
" answer.append((word,translated_word)) # dodanie do odpowiedzi m razy\n",
" \n",
" return answer\n",
"\n",
"glossary_lookup('drukarka - Każda drukarka posiada przycisk wznowienia drukowania')"
] ]
} }
], ],
@ -452,7 +557,7 @@
"author": "Rafał Jaworski", "author": "Rafał Jaworski",
"email": "rjawor@amu.edu.pl", "email": "rjawor@amu.edu.pl",
"kernelspec": { "kernelspec": {
"display_name": "Python 3", "display_name": "Python 3 (ipykernel)",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
}, },
@ -467,7 +572,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.8.10" "version": "3.9.2"
}, },
"subtitle": "1. Podstawowe techniki wspomagania tłumaczenia", "subtitle": "1. Podstawowe techniki wspomagania tłumaczenia",
"title": "Komputerowe wspomaganie tłumaczenia", "title": "Komputerowe wspomaganie tłumaczenia",

234
lab/lab_02.ipynb
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@ -57,7 +57,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 3,
"id": "confident-prison", "id": "confident-prison",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -80,13 +80,102 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 21,
"id": "continental-submission", "id": "continental-submission",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"['Wciśnij przycisk Enter']"
]
},
"execution_count": 21,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"def tm_lookup(sentence):\n",
" return [entry[1] for entry in translation_memory if entry[0].lower() == sentence.lower()]\n",
"\n",
"def ice_lookup(sentence, prev_sentence, next_sentence):\n", "def ice_lookup(sentence, prev_sentence, next_sentence):\n",
" return []" " if (not prev_sentence) or (not next_sentence):\n",
" return 'no context'\n",
" \n",
" if not sentence:\n",
" return 'enter your sentence'\n",
" \n",
" #Dobrze prawie ale tutaj zwracane są listy. wszystko okey, gdy zdanie poprzedzające i następne mają tamą ilość słów. JEST zdecydowanie błędny gdy zdania mają różną ilość słów!\n",
" if tm_lookup(prev_sentence) and tm_lookup(next_sentence):\n",
" return [entry[0] for entry in translation_memory if entry[0].lower() == sentence.lower()]\n",
" else:\n",
" return \"\"\n",
" \n",
"ice_lookup('Wciśnij przycisk Enter','Sprawdź ustawienia sieciowe','Drukarka jest wyłączona')"
]
},
{
"cell_type": "code",
"execution_count": 18,
"id": "ecb19925-7467-4e8a-bfdf-9adee52a5894",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'no context'"
]
},
"execution_count": 18,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ice_lookup('Wciśnij przycisk Enter','Sprawdź ustawienia sieciowe','')"
]
},
{
"cell_type": "code",
"execution_count": 19,
"id": "cf60a398-ae06-4ca8-b658-e011632cdb33",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'enter your sentence'"
]
},
"execution_count": 19,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ice_lookup('','Sprawdź ustawienia sieciowe','Drukarka jest wyłączona')"
]
},
{
"cell_type": "code",
"execution_count": 20,
"id": "d34415a4-d853-435e-b093-fabc4629ff26",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'no context'"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"ice_lookup('Wciśnij przycisk Enter','','Drukarka jest wyłączona')"
] ]
}, },
{ {
@ -141,7 +230,13 @@
"id": "graduate-theorem", "id": "graduate-theorem",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Odpowiedź:" "### Odpowiedź:\n",
"- 1. **spełnia warunek**: dzięki zastosowaniu funkcji `abs()`\n",
"- 3. **spełnia warunek**: przemienność w tym przypadku również zawdzięczamy funkcj `abs()`\n",
"- 4. **spełnia warunek**:(z uproszczeniem że x i y i z to len(z danej zmiennej) -> |y-x| + |z-y| >= |z-x| =\n",
"- = |y - y - x + z| >= |z-x| = |z-x| >= |z-x|\n",
"\n",
"2 nie jest spełnione, ponieważ x i y muszą być tymi samymi zdaniami aby odległość była równa 0. A wyżej wymieniona funckja spełnia ten warunek dla wszytskich zdań które mają taką samą ilość znaków."
] ]
}, },
{ {
@ -179,7 +274,11 @@
"id": "metallic-leave", "id": "metallic-leave",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Odpowiedź:" "### Odpowiedź:\n",
"- 1. **spełnia warunek**, ponieważ zwróci wartość 0 lub 3 które są >= 0\n",
"- 2. **spełnia waurenk**, ponieważ gdy zdanie x jest takie samo jak y = to odległość jest zwracana jako 0\n",
"- 3. **spełnia warunek**, ponieważ sprawdzenia wygląda w taki sposób, że porównujemy czy x == y (co jest tożsame z y == x) w przeciwnym wypadku zawsze zwracamy tą samą wartość\n",
"- 4. **spełnia warunek**, ponieważ gdy xyz są takie same to mamy 0>=0 | gdy wszystkie są różne to mamy 6>=3 | gdy jedna para się różni 6>=0 lub 3>=0"
] ]
}, },
{ {
@ -206,7 +305,12 @@
"id": "bibliographic-stopping", "id": "bibliographic-stopping",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Odpowiedź:" "### Odpowiedź: Jest funckją dystansu\n",
"- 1. **spełnia warunek** Liczba wymaganych operacji edycyjnych nie może być mniejsza niż zero. W przypadku gdy zdania są sobie równe d(x,y) = 0\n",
"- 2. **spełnia warunek** Gdy zdania są sobie równe d(x,y) = 0\n",
"- 3. **spełnia warunek** nie ważne czy zrobimy d(x,y) czy d(y,x) nadal liczba operacji edycyjnych będzie taka sama pa->papa (+2) | papa -> pa (-2)\n",
"- 4. **spełnia warunek**: (z uproszczeniem że x i y i z to liczba wymaganych zmian -> |y?x| + |z?y| >= |z?x| =\n",
"- = x + y >= x"
] ]
}, },
{ {
@ -223,7 +327,38 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 1,
"id": "727b188d-eedd-4d19-9cbf-efcce71e145c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"Collecting python-Levenshtein\n",
" Downloading python_Levenshtein-0.25.1-py3-none-any.whl.metadata (3.7 kB)\n",
"Collecting Levenshtein==0.25.1 (from python-Levenshtein)\n",
" Downloading Levenshtein-0.25.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (3.3 kB)\n",
"Collecting rapidfuzz<4.0.0,>=3.8.0 (from Levenshtein==0.25.1->python-Levenshtein)\n",
" Downloading rapidfuzz-3.8.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.metadata (11 kB)\n",
"Downloading python_Levenshtein-0.25.1-py3-none-any.whl (9.4 kB)\n",
"Downloading Levenshtein-0.25.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (177 kB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m177.4/177.4 kB\u001b[0m \u001b[31m3.6 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m\n",
"\u001b[?25hDownloading rapidfuzz-3.8.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.4 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m3.4/3.4 MB\u001b[0m \u001b[31m40.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m00:01\u001b[0m\n",
"\u001b[?25hInstalling collected packages: rapidfuzz, Levenshtein, python-Levenshtein\n",
"Successfully installed Levenshtein-0.25.1 python-Levenshtein-0.25.1 rapidfuzz-3.8.1\n"
]
}
],
"source": [
"pip3 install python-Levenshtein"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "secondary-wrist", "id": "secondary-wrist",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -233,7 +368,7 @@
"2" "2"
] ]
}, },
"execution_count": 5, "execution_count": 17,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -254,7 +389,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 18,
"id": "associate-tuner", "id": "associate-tuner",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -273,7 +408,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 7, "execution_count": 3,
"id": "focal-pathology", "id": "focal-pathology",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -283,7 +418,7 @@
"0.9166666666666666" "0.9166666666666666"
] ]
}, },
"execution_count": 7, "execution_count": 3,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -294,7 +429,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 4,
"id": "roman-ceiling", "id": "roman-ceiling",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -304,7 +439,7 @@
"0.9428571428571428" "0.9428571428571428"
] ]
}, },
"execution_count": 8, "execution_count": 4,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -315,7 +450,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": 5,
"id": "invisible-cambodia", "id": "invisible-cambodia",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -325,7 +460,7 @@
"0.631578947368421" "0.631578947368421"
] ]
}, },
"execution_count": 9, "execution_count": 5,
"metadata": {}, "metadata": {},
"output_type": "execute_result" "output_type": "execute_result"
} }
@ -344,21 +479,80 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 10, "execution_count": 37,
"id": "genetic-cradle", "id": "genetic-cradle",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"def fuzzy_lookup(sentence, threshold):\n", "def fuzzy_lookup(sentence, threshold):\n",
" return []" " \n",
" answer = []\n",
" \n",
" for entry in translation_memory:\n",
" if levenshtein_similarity(sentence.lower(),entry[0].lower()) >= threshold:\n",
" answer.append(entry[1])\n",
" \n",
" return answer"
] ]
},
{
"cell_type": "code",
"execution_count": 40,
"id": "cc0544a4-a515-4515-a116-f13b96e92812",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Press the ENTER button']"
]
},
"execution_count": 40,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#'Wciśnij przycisk Enter'\n",
"fuzzy_lookup('KlikNiJ przycisK EnTeR', 0.86)"
]
},
{
"cell_type": "code",
"execution_count": 41,
"id": "e2b8ff91-a103-45a4-a746-8ce3e9470c4c",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"['Check the network settings']"
]
},
"execution_count": 41,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"#'Sprawdź ustawienia sieciowe'\n",
"fuzzy_lookup('Sprawdź ustawienia sieci', 0.885)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "df759469-b92e-490c-a672-96bd4c0d76b2",
"metadata": {},
"outputs": [],
"source": []
} }
], ],
"metadata": { "metadata": {
"author": "Rafał Jaworski", "author": "Rafał Jaworski",
"email": "rjawor@amu.edu.pl", "email": "rjawor@amu.edu.pl",
"kernelspec": { "kernelspec": {
"display_name": "Python 3", "display_name": "Python 3 (ipykernel)",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
}, },
@ -373,7 +567,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.8.10" "version": "3.9.2"
}, },
"subtitle": "2. Zaawansowane użycie pamięci tłumaczeń", "subtitle": "2. Zaawansowane użycie pamięci tłumaczeń",
"title": "Komputerowe wspomaganie tłumaczenia", "title": "Komputerowe wspomaganie tłumaczenia",

371
lab/lab_03.ipynb
View File

@ -20,6 +20,13 @@
"id": "aggregate-listing", "id": "aggregate-listing",
"metadata": {}, "metadata": {},
"source": [ "source": [
"```python\n",
"import collections\n",
"lista1 = [3,4,5,4,4,7,8,7]\n",
"lista2 = [3,4,5,4,4,7,8,7]\n",
"print((collections.Counter(lista) + collections.Counter(lista2)).most_common(5))\n",
"```\n",
"\n",
"Na dzisiejszych zajęciach zajmiemy się bliżej słownikami używanymi do wspomagania tłumaczenia. Oczywiście na rynku dostępnych jest bardzo wiele słowników w formacie elektronicznym. Wiele z nich jest gotowych do użycia w SDL Trados, memoQ i innych narzędziach CAT. Zawierają one setki tysięcy lub miliony haseł i oferują natychmiastową pomoc tłumaczowi." "Na dzisiejszych zajęciach zajmiemy się bliżej słownikami używanymi do wspomagania tłumaczenia. Oczywiście na rynku dostępnych jest bardzo wiele słowników w formacie elektronicznym. Wiele z nich jest gotowych do użycia w SDL Trados, memoQ i innych narzędziach CAT. Zawierają one setki tysięcy lub miliony haseł i oferują natychmiastową pomoc tłumaczowi."
] ]
}, },
@ -63,7 +70,12 @@
"id": "diverse-sunglasses", "id": "diverse-sunglasses",
"metadata": {}, "metadata": {},
"source": [ "source": [
"Odpowiedź:" "### Odpowiedź:\n",
"- **DeepL:** metal cabinet slides / metal cabinet guides\n",
"- **Model GPT-3.5:** metal cabinet slides / metal wardrobe rails.\n",
"- **Model GPT-4:** guides for metal cabinets / metal cabinet guides\n",
"- **Google-translate**: metal cabinet guides\n",
"- **www.tlumaczangielskopolski.pl:** metal cabinet guides\n"
] ]
}, },
{ {
@ -86,7 +98,7 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 1, "execution_count": 70,
"id": "loving-prince", "id": "loving-prince",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
@ -110,12 +122,12 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 2, "execution_count": 71,
"id": "bound-auction", "id": "bound-auction",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [],
"source": [ "source": [
"dictionary = ['program', 'application', 'applet' 'compile']" "dictionary = ['program', 'application', 'applet', 'compile']"
] ]
}, },
{ {
@ -128,13 +140,46 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 3, "execution_count": 76,
"id": "cognitive-cedar", "id": "cognitive-cedar",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"{'applet': [(302, 308)],\n",
" 'application': [(80, 91), (153, 84), (300, 158)],\n",
" 'compile': [(56, 63), (497, 448)],\n",
" 'program': [(14, 21), (284, 277), (454, 177), (495, 48), (505, 17)]}\n"
]
}
],
"source": [ "source": [
"import re\n",
"from pprint import pprint\n",
"\n",
"def terminology_lookup():\n", "def terminology_lookup():\n",
" return []" " answer = {pattern:[] for pattern in dictionary}\n",
" low_text = text.lower()\n",
" for pattern in dictionary:\n",
" offset = 0\n",
" start = 0\n",
" end = 0\n",
" while True:\n",
" match = (re.search(pattern,low_text[offset:]))\n",
" if not match:\n",
" break\n",
" else:\n",
" start += match.start()\n",
" end = +match.end()\n",
" offset += end\n",
"\n",
" answer[pattern].append((start,end))\n",
" pprint(answer)\n",
" #return answer\n",
"\n",
"terminology_lookup()"
] ]
}, },
{ {
@ -161,7 +206,113 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 4, "execution_count": 1,
"id": "02e1c16f-be37-4a64-a514-8875b393ccb7",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"Requirement already satisfied: spacy in /usr/local/lib/python3.9/dist-packages (3.4.1)\n",
"Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.9 in /usr/local/lib/python3.9/dist-packages (from spacy) (3.0.10)\n",
"Requirement already satisfied: spacy-loggers<2.0.0,>=1.0.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (1.0.3)\n",
"Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (1.0.8)\n",
"Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.9/dist-packages (from spacy) (2.0.6)\n",
"Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.9/dist-packages (from spacy) (3.0.7)\n",
"Requirement already satisfied: thinc<8.2.0,>=8.1.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (8.1.1)\n",
"Requirement already satisfied: wasabi<1.1.0,>=0.9.1 in /usr/local/lib/python3.9/dist-packages (from spacy) (0.10.1)\n",
"Requirement already satisfied: srsly<3.0.0,>=2.4.3 in /usr/local/lib/python3.9/dist-packages (from spacy) (2.4.4)\n",
"Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /usr/local/lib/python3.9/dist-packages (from spacy) (2.0.8)\n",
"Requirement already satisfied: typer<0.5.0,>=0.3.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (0.4.2)\n",
"Requirement already satisfied: pathy>=0.3.5 in /usr/local/lib/python3.9/dist-packages (from spacy) (0.6.2)\n",
"Requirement already satisfied: tqdm<5.0.0,>=4.38.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (4.64.1)\n",
"Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (1.21.6)\n",
"Requirement already satisfied: requests<3.0.0,>=2.13.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (2.28.1)\n",
"Requirement already satisfied: pydantic!=1.8,!=1.8.1,<1.10.0,>=1.7.4 in /usr/local/lib/python3.9/dist-packages (from spacy) (1.9.2)\n",
"Requirement already satisfied: jinja2 in /usr/local/lib/python3.9/dist-packages (from spacy) (3.1.2)\n",
"Requirement already satisfied: setuptools in /usr/lib/python3/dist-packages (from spacy) (52.0.0)\n",
"Requirement already satisfied: packaging>=20.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (21.3)\n",
"Requirement already satisfied: langcodes<4.0.0,>=3.2.0 in /usr/local/lib/python3.9/dist-packages (from spacy) (3.3.0)\n",
"Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in /usr/lib/python3/dist-packages (from packaging>=20.0->spacy) (2.4.7)\n",
"Requirement already satisfied: smart-open<6.0.0,>=5.2.1 in /usr/local/lib/python3.9/dist-packages (from pathy>=0.3.5->spacy) (5.2.1)\n",
"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.9/dist-packages (from pydantic!=1.8,!=1.8.1,<1.10.0,>=1.7.4->spacy) (4.3.0)\n",
"Requirement already satisfied: charset-normalizer<3,>=2 in /usr/local/lib/python3.9/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (2.1.1)\n",
"Requirement already satisfied: idna<4,>=2.5 in /usr/local/lib/python3.9/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (3.4)\n",
"Requirement already satisfied: urllib3<1.27,>=1.21.1 in /usr/local/lib/python3.9/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (1.26.12)\n",
"Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.9/dist-packages (from requests<3.0.0,>=2.13.0->spacy) (2022.9.14)\n",
"Requirement already satisfied: blis<0.10.0,>=0.7.8 in /usr/local/lib/python3.9/dist-packages (from thinc<8.2.0,>=8.1.0->spacy) (0.9.1)\n",
"Requirement already satisfied: confection<1.0.0,>=0.0.1 in /usr/local/lib/python3.9/dist-packages (from thinc<8.2.0,>=8.1.0->spacy) (0.0.1)\n",
"Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.9/dist-packages (from typer<0.5.0,>=0.3.0->spacy) (8.1.3)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.9/dist-packages (from jinja2->spacy) (2.1.1)\n"
]
}
],
"source": [
"pip3 install spacy"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "f6d7e9f5-4d6f-49c5-8dea-9957bc6da318",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Defaulting to user installation because normal site-packages is not writeable\n",
"\u001b[33mDEPRECATION: https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.4.1/en_core_web_sm-3.4.1-py3-none-any.whl#egg=en_core_web_sm==3.4.1 contains an egg fragment with a non-PEP 508 name pip 25.0 will enforce this behaviour change. A possible replacement is to use the req @ url syntax, and remove the egg fragment. Discussion can be found at https://github.com/pypa/pip/issues/11617\u001b[0m\u001b[33m\n",
"\u001b[0mCollecting en-core-web-sm==3.4.1\n",
" Downloading https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.4.1/en_core_web_sm-3.4.1-py3-none-any.whl (12.8 MB)\n",
"\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m12.8/12.8 MB\u001b[0m \u001b[31m45.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m00:01\u001b[0m0:01\u001b[0m\n",
"\u001b[?25hRequirement already satisfied: spacy<3.5.0,>=3.4.0 in /usr/local/lib/python3.9/dist-packages (from en-core-web-sm==3.4.1) (3.4.1)\n",
"Requirement already satisfied: spacy-legacy<3.1.0,>=3.0.9 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (3.0.10)\n",
"Requirement already satisfied: spacy-loggers<2.0.0,>=1.0.0 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (1.0.3)\n",
"Requirement already satisfied: murmurhash<1.1.0,>=0.28.0 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (1.0.8)\n",
"Requirement already satisfied: cymem<2.1.0,>=2.0.2 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (2.0.6)\n",
"Requirement already satisfied: preshed<3.1.0,>=3.0.2 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (3.0.7)\n",
"Requirement already satisfied: thinc<8.2.0,>=8.1.0 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (8.1.1)\n",
"Requirement already satisfied: wasabi<1.1.0,>=0.9.1 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (0.10.1)\n",
"Requirement already satisfied: srsly<3.0.0,>=2.4.3 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (2.4.4)\n",
"Requirement already satisfied: catalogue<2.1.0,>=2.0.6 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (2.0.8)\n",
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"Requirement already satisfied: numpy>=1.15.0 in /usr/local/lib/python3.9/dist-packages (from spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (1.21.6)\n",
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"Requirement already satisfied: typing-extensions>=3.7.4.3 in /usr/local/lib/python3.9/dist-packages (from pydantic!=1.8,!=1.8.1,<1.10.0,>=1.7.4->spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (4.3.0)\n",
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"Requirement already satisfied: confection<1.0.0,>=0.0.1 in /usr/local/lib/python3.9/dist-packages (from thinc<8.2.0,>=8.1.0->spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (0.0.1)\n",
"Requirement already satisfied: click<9.0.0,>=7.1.1 in /usr/local/lib/python3.9/dist-packages (from typer<0.5.0,>=0.3.0->spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (8.1.3)\n",
"Requirement already satisfied: MarkupSafe>=2.0 in /usr/local/lib/python3.9/dist-packages (from jinja2->spacy<3.5.0,>=3.4.0->en-core-web-sm==3.4.1) (2.1.1)\n",
"Installing collected packages: en-core-web-sm\n",
"Successfully installed en-core-web-sm-3.4.1\n",
"\u001b[38;5;2m✔ Download and installation successful\u001b[0m\n",
"You can now load the package via spacy.load('en_core_web_sm')\n"
]
}
],
"source": [
"python3 -m spacy download en_core_web_sm"
]
},
{
"cell_type": "code",
"execution_count": 15,
"id": "tribal-attention", "id": "tribal-attention",
"metadata": {}, "metadata": {},
"outputs": [ "outputs": [
@ -232,7 +383,7 @@
"be\n", "be\n",
"the\n", "the\n",
"step\n", "step\n",
"-PRON-\n", "you\n",
"need\n", "need\n",
"to\n", "to\n",
"follow\n", "follow\n",
@ -248,7 +399,7 @@
"platform\n", "platform\n",
",\n", ",\n",
"if\n", "if\n",
"-PRON-\n", "you\n",
"have\n", "have\n",
"not\n", "not\n",
"already\n", "already\n",
@ -260,7 +411,7 @@
"program\n", "program\n",
"that\n", "that\n",
"use\n", "use\n",
"Swing\n", "swing\n",
"component\n", "component\n",
".\n", ".\n",
"compile\n", "compile\n",
@ -302,13 +453,37 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 5, "execution_count": 20,
"id": "surgical-demonstration", "id": "surgical-demonstration",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"{'program': [(14, 24), (291, 298), (468, 475), (516, 523), (533, 540)],\n",
" 'application': [(80, 91), (164, 175), (322, 333)],\n",
" 'applet': [(302, 308)],\n",
" 'compile': [(56, 63), (134, 141), (504, 511)]}"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"import re\n",
"\n",
"def terminology_lookup():\n", "def terminology_lookup():\n",
" return []" " answer = {pattern:[] for pattern in dictionary}\n",
"\n",
" for pattern in dictionary:\n",
" for token in doc:\n",
" if pattern in token.lemma_:\n",
" answer[pattern].append((token.idx,token.idx+len(token.lemma_)))\n",
" return answer\n",
"\n",
"terminology_lookup()"
] ]
}, },
{ {
@ -337,13 +512,52 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 6, "execution_count": 73,
"id": "superb-butterfly", "id": "superb-butterfly",
"metadata": {}, "metadata": {},
"outputs": [], "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",
" 'Swing',\n",
" 'programs',\n",
" 'applets',\n",
" 'applications',\n",
" 'steps',\n",
" 'release',\n",
" 'platform',\n",
" 'program',\n",
" 'Swing',\n",
" 'components',\n",
" 'program',\n",
" 'program']"
]
},
"execution_count": 73,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"import spacy\n",
"def get_nouns(text):\n", "def get_nouns(text):\n",
" return []" " nlp = spacy.load(\"en_core_web_sm\")\n",
" doc = nlp(text)\n",
" nouns = [token.text for token in doc if token.pos_ == \"NOUN\"]\n",
" return nouns\n",
"\n",
"get_nouns(text)"
] ]
}, },
{ {
@ -374,13 +588,51 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 8, "execution_count": 74,
"id": "eight-redhead", "id": "eight-redhead",
"metadata": {}, "metadata": {},
"outputs": [], "outputs": [
{
"data": {
"text/plain": [
"{'programmer': 1,\n",
" 'section': 1,\n",
" 'swing': 4,\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": 74,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [ "source": [
"from collections import Counter\n",
"import spacy\n",
"\n",
"def extract_terms(text):\n", "def extract_terms(text):\n",
" return []" " nlp = spacy.load(\"en_core_web_sm\")\n",
" doc = nlp(text)\n",
" tally = {}\n",
" nouns = [token.lemma_ for token in doc if token.pos_ == \"NOUN\"]\n",
" nouns_counts = Counter(nouns)\n",
" \n",
" for word, count in nouns_counts.items():\n",
" tally.update({word: count})\n",
" return tally\n",
"\n",
"extract_terms(text)"
] ]
}, },
{ {
@ -393,13 +645,82 @@
}, },
{ {
"cell_type": "code", "cell_type": "code",
"execution_count": 9, "execution_count": 75,
"id": "monetary-mambo", "id": "monetary-mambo",
"metadata": {}, "metadata": {},
"outputs": [], "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': 4},\n",
" 'verbs': {'compile': 3,\n",
" 'create': 1,\n",
" 'do': 1,\n",
" 'explain': 1,\n",
" 'follow': 1,\n",
" 'install': 1,\n",
" 'need': 1,\n",
" 'run': 3,\n",
" 'see': 1,\n",
" 'use': 2,\n",
" 'work': 1}}\n"
]
}
],
"source": [ "source": [
"from pprint import pprint\n",
"from collections import Counter\n",
"import spacy\n",
"\n",
"def extract_terms(text):\n", "def extract_terms(text):\n",
" return []" " \n",
" nlp = spacy.load(\"en_core_web_sm\")\n",
" doc = nlp(text)\n",
" \n",
" nouns, verbs, adjectives = [], [], []\n",
" tally = {\"nouns\": {}, \"verbs\": {}, \"adjectives\": {}}\n",
" \n",
" for token in doc:\n",
" if token.pos_ == \"NOUN\":\n",
" nouns.append(token.lemma_)\n",
" elif token.pos_ == \"VERB\":\n",
" verbs.append(token.lemma_)\n",
" elif token.pos_ == \"ADJ\":\n",
" adjectives.append(token.lemma_)\n",
" \n",
" nouns_counts = Counter(nouns)\n",
" verbs_counts = Counter(verbs)\n",
" adjectives_counts = Counter(adjectives)\n",
"\n",
" for word, count in nouns_counts.items():\n",
" tally[\"nouns\"].update({word: count})\n",
" \n",
" for word, count in verbs_counts.items():\n",
" tally[\"verbs\"].update({word: count})\n",
" \n",
" for word, count in adjectives_counts.items():\n",
" tally[\"adjectives\"].update({word: count})\n",
"\n",
" pprint(tally)\n",
" #return tally\n",
"\n",
"extract_terms(text)"
] ]
} }
], ],
@ -407,7 +728,7 @@
"author": "Rafał Jaworski", "author": "Rafał Jaworski",
"email": "rjawor@amu.edu.pl", "email": "rjawor@amu.edu.pl",
"kernelspec": { "kernelspec": {
"display_name": "Python 3", "display_name": "Python 3 (ipykernel)",
"language": "python", "language": "python",
"name": "python3" "name": "python3"
}, },
@ -422,7 +743,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.8.10" "version": "3.9.2"
}, },
"subtitle": "3. Terminologia", "subtitle": "3. Terminologia",
"title": "Komputerowe wspomaganie tłumaczenia", "title": "Komputerowe wspomaganie tłumaczenia",