forked from bfijalkowski/KWT-2024
Laboratoria 13.04.2024
This commit is contained in:
Marek Susniak
parent
71ca3b66ed
commit
957bd22d58
162
lab/lab_01.ipynb
162
lab/lab_01.ipynb
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@ -52,7 +52,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 77,
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"id": "narrow-romantic",
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"metadata": {},
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"outputs": [],
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@ -71,7 +71,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 78,
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"id": "indonesian-electron",
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"metadata": {},
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"outputs": [],
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@ -82,7 +82,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 79,
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"id": "compact-trinidad",
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"metadata": {},
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"outputs": [
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@ -92,7 +92,7 @@
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"['Press the ENTER button']"
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]
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},
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"execution_count": 3,
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"execution_count": 79,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -119,7 +119,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 80,
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"id": "exposed-daniel",
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"metadata": {},
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"outputs": [],
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@ -139,7 +139,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 81,
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"id": "serial-velvet",
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"metadata": {},
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"outputs": [
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@ -149,7 +149,7 @@
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"['Press the ENTER button', 'Press the ENTER key']"
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]
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},
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"execution_count": 5,
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"execution_count": 81,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -176,7 +176,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 82,
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"id": "every-gibson",
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"metadata": {},
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"outputs": [
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@ -186,7 +186,7 @@
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"[]"
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]
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},
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"execution_count": 6,
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"execution_count": 82,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -213,13 +213,15 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": 83,
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"id": "protected-rings",
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"metadata": {},
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"outputs": [],
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"source": [
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"def tm_lookup(sentence):\n",
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" return ''"
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" lowerSentence = sentence.lower()\n",
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"\n",
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" return [entry[1] for entry in translation_memory if entry[0].lower() == lowerSentence]"
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]
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},
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{
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@ -232,17 +234,17 @@
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},
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{
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"cell_type": "code",
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"execution_count": 18,
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"id": "severe-alloy",
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"execution_count": 84,
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"id": "60a6c976",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"''"
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"[]"
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]
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},
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"execution_count": 18,
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"execution_count": 84,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -261,13 +263,21 @@
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},
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{
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"cell_type": "code",
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"execution_count": 11,
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"execution_count": 85,
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"id": "structural-diesel",
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"metadata": {},
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"outputs": [],
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"source": [
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"import string\n",
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"\n",
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"def prepare_sentence(sentence):\n",
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" translator = str.maketrans('', '', string.punctuation)\n",
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"\n",
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" return sentence.lower().translate(translator)\n",
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"\n",
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"def tm_lookup(sentence):\n",
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" return ''"
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" lowerSentence = prepare_sentence(sentence)\n",
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" return [entry[1] for entry in translation_memory if prepare_sentence(entry[0]) == lowerSentence]"
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]
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},
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{
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@ -280,17 +290,17 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 86,
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"id": "brief-senegal",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"''"
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"[]"
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]
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},
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"execution_count": 12,
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"execution_count": 86,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -317,13 +327,43 @@
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 87,
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"id": "mathematical-customs",
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"metadata": {},
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"outputs": [],
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"source": [
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"import string\n",
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"\n",
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"def prepare_sentence(sentence):\n",
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" translator = str.maketrans('', '', string.punctuation)\n",
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"\n",
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" return sentence.lower().translate(translator)\n",
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"\n",
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"def sentence_similar(sentence1, sentence2):\n",
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" words1 = sentence1.split()\n",
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" words2 = sentence2.split()\n",
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" \n",
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" min_length = min(len(words1), len(words2))\n",
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" \n",
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" matched_count = 0\n",
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" for i in range(min_length):\n",
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" if prepare_sentence(words1[i]) == prepare_sentence(words2[i]):\n",
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" matched_count += 1\n",
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" \n",
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" return {\n",
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" \"count\": matched_count,\n",
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" \"length\": min_length\n",
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" }\n",
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"\n",
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"def tm_lookup(sentence):\n",
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" return ''"
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" collection = []\n",
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"\n",
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" for entry in translation_memory:\n",
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" similarity = sentence_similar(sentence, entry[0])\n",
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" if similarity[\"length\"] - similarity[\"count\"] <= 1:\n",
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" collection.append(entry[1])\n",
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"\n",
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" return collection\n"
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]
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},
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{
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@ -344,7 +384,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 15,
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"execution_count": 88,
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"id": "humanitarian-wrong",
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"metadata": {},
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"outputs": [],
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@ -362,7 +402,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 89,
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"id": "located-perception",
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"metadata": {},
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"outputs": [],
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@ -374,7 +414,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 17,
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"execution_count": 90,
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"id": "advised-casting",
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"metadata": {},
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"outputs": [
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@ -384,7 +424,7 @@
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"[('przycisk', 'button'), ('drukarka', 'printer')]"
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]
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},
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"execution_count": 17,
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"execution_count": 90,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -406,7 +446,7 @@
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"id": "defensive-fifteen",
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"metadata": {},
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"source": [
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"Odpowiedź:"
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"Odpowiedź: Jest to n przeszukiwań po liście m-elementowej co daje złozonosc O(n*m)"
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]
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},
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{
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@ -419,13 +459,40 @@
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},
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{
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"cell_type": "code",
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"execution_count": 19,
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"execution_count": 91,
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"id": "original-tunisia",
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"metadata": {},
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"outputs": [],
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"source": [
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"def prepare_sentence(sentence):\n",
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" return sentence.lower()\n",
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"\n",
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"def glossary_lookup(sentence):\n",
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" return ''"
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" sentence_words = sentence.split()\n",
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" lowered_words = list(map(prepare_sentence, sentence_words))\n",
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"\n",
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" return [entry for entry in glossary if prepare_sentence(entry[0]) in lowered_words]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 92,
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"id": "df948bb3",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[('komputer', 'computer')]"
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]
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},
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"execution_count": 92,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"glossary_lookup(\"Komputer\")"
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]
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},
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{
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@ -438,13 +505,44 @@
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},
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{
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"cell_type": "code",
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"execution_count": 20,
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"execution_count": 93,
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"id": "adolescent-semiconductor",
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"metadata": {},
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"outputs": [],
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"source": [
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"def prepare_dictionary(sentences):\n",
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" dict = {}\n",
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"\n",
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" for entry in sentences:\n",
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" dict[entry[0].lower()] = entry\n",
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"\n",
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" return dict\n",
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"\n",
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"glossary_dict = prepare_dictionary(glossary)\n",
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"\n",
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"def glossary_lookup(sentence):\n",
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" return ''"
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" return glossary_dict[sentence.lower()]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 94,
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"id": "98e9ff56",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"('komputer', 'computer')"
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]
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},
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"execution_count": 94,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"glossary_lookup(\"Komputer\")"
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]
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}
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],
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@ -467,7 +565,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.8.10"
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"version": "3.7.9"
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},
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"subtitle": "1. Podstawowe techniki wspomagania tłumaczenia",
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"title": "Komputerowe wspomaganie tłumaczenia",
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131
lab/lab_02.ipynb
131
lab/lab_02.ipynb
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@ -57,7 +57,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"execution_count": 92,
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"id": "confident-prison",
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"metadata": {},
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"outputs": [],
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@ -80,15 +80,51 @@
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"execution_count": 93,
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"id": "continental-submission",
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"metadata": {},
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"outputs": [],
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"source": [
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"def ice_lookup(sentence, prev_sentence, next_sentence):\n",
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"def prepare_dictionary(sentences):\n",
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" dict = {}\n",
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"\n",
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" for entry in sentences:\n",
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" dict[entry[0].lower()] = entry\n",
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"\n",
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" return dict\n",
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"\n",
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"memory_dict = prepare_dictionary(translation_memory)\n",
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"\n",
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"def ice_lookup(input, prev_sentence, next_sentence): \n",
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" sentence = input.lower()\n",
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"\n",
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" if prev_sentence.lower() in memory_dict and next_sentence.lower() in memory_dict and sentence in memory_dict:\n",
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" return memory_dict[sentence]\n",
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"\n",
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" return []"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 94,
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"id": "bdc1df76",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"('Wciśnij przycisk Enter', 'Press the ENTER button')"
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]
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},
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"execution_count": 94,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"ice_lookup(\"Wciśnij przycisk Enter\", \"Sprawdź ustawienia sieciowe\", \"Drukarka jest wyłączona\")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "figured-server",
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@ -119,7 +155,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 3,
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"execution_count": 95,
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"id": "fourth-pillow",
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"metadata": {},
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"outputs": [],
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"id": "graduate-theorem",
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"metadata": {},
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"source": [
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"Odpowiedź:"
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"Odpowiedź: Nie, nie jest poprawna. Cechy:\n",
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"- nieujemna (abs > 0)\n",
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"- identyfikacja nie jest spelniona -> moga miec taka sama dlugosc, a byc inne\n",
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"- symetryczna - wynik z wartosci bezwglednej\n",
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"- nierownosc trojkata nie jest spelniona"
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]
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},
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{
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@ -154,7 +194,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"execution_count": 96,
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"id": "continued-christopher",
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"metadata": {},
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"outputs": [],
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@ -179,7 +219,7 @@
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"id": "metallic-leave",
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"metadata": {},
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"source": [
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"Odpowiedź:"
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"Odpowiedź: z punktu widzenia cech, wszystkie cechy sa spelnione, jednak funkcja sama w sobie jest bezuyteczna poprzez to, ze wartosci sa stale. "
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]
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},
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{
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@ -206,7 +246,10 @@
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"id": "bibliographic-stopping",
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"metadata": {},
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"source": [
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"Odpowiedź:"
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"Odpowiedź: Tak, poniewaz spelnia cechy: \n",
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"- nieujemnosci - zawsze dodatni lub zero gdy a i b jest rowny sobie\n",
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"- symetria - dystans od a i b jest taki sam jak b i a\n",
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"- nierownosc trojkata - dystans od ciągu A do C przez B jest zawsze mniejszy lub równy sumie dystansów od A do B i od B do C"
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]
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},
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{
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@ -223,7 +266,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 5,
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"execution_count": 97,
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"id": "secondary-wrist",
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"metadata": {},
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"outputs": [
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@ -233,7 +276,7 @@
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"2"
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]
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},
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"execution_count": 5,
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"execution_count": 97,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -254,7 +297,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": 98,
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"id": "associate-tuner",
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"metadata": {},
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"outputs": [],
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@ -273,7 +316,7 @@
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},
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{
|
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"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"execution_count": 99,
|
||||
"id": "focal-pathology",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
|
@ -283,7 +326,7 @@
|
|||
"0.9166666666666666"
|
||||
]
|
||||
},
|
||||
"execution_count": 7,
|
||||
"execution_count": 99,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -294,7 +337,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"execution_count": 100,
|
||||
"id": "roman-ceiling",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
|
@ -304,7 +347,7 @@
|
|||
"0.9428571428571428"
|
||||
]
|
||||
},
|
||||
"execution_count": 8,
|
||||
"execution_count": 100,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -315,7 +358,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"execution_count": 101,
|
||||
"id": "invisible-cambodia",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
|
@ -325,7 +368,7 @@
|
|||
"0.631578947368421"
|
||||
]
|
||||
},
|
||||
"execution_count": 9,
|
||||
"execution_count": 101,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
|
|
@ -344,13 +387,61 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 10,
|
||||
"execution_count": 102,
|
||||
"id": "genetic-cradle",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def fuzzy_lookup(sentence, threshold):\n",
|
||||
" return []"
|
||||
" col = []\n",
|
||||
"\n",
|
||||
" for entry in translation_memory:\n",
|
||||
" if (levenshtein_similarity(entry[0], sentence)) >= threshold:\n",
|
||||
" col.append(entry)\n",
|
||||
" \n",
|
||||
" return col"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 103,
|
||||
"id": "57fb39b9",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[]"
|
||||
]
|
||||
},
|
||||
"execution_count": 103,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"fuzzy_lookup('Spróbuj wyłączyć i włączyć komputer', 0.7)"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 104,
|
||||
"id": "94e1b3be",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[('Wciśnij przycisk Enter', 'Press the ENTER button')]"
|
||||
]
|
||||
},
|
||||
"execution_count": 104,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"fuzzy_lookup('Wciśnij przycisk escape', 0.7)"
|
||||
]
|
||||
}
|
||||
],
|
||||
|
|
@ -373,7 +464,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.10"
|
||||
"version": "3.7.9"
|
||||
},
|
||||
"subtitle": "2. Zaawansowane użycie pamięci tłumaczeń",
|
||||
"title": "Komputerowe wspomaganie tłumaczenia",
|
||||
|
|
|
|||
|
|
@ -86,7 +86,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"execution_count": 31,
|
||||
"id": "loving-prince",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
@ -110,12 +110,12 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"execution_count": 32,
|
||||
"id": "bound-auction",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"dictionary = ['program', 'application', 'applet' 'compile']"
|
||||
"dictionary = ['program', 'application', 'applet', 'compile']"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -128,13 +128,47 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 3,
|
||||
"execution_count": 33,
|
||||
"id": "cognitive-cedar",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"def terminology_lookup():\n",
|
||||
" return []"
|
||||
"import re\n",
|
||||
"\n",
|
||||
"def terminology_lookup(txt, labels):\n",
|
||||
" results = []\n",
|
||||
"\n",
|
||||
" for label in labels:\n",
|
||||
" results.append((\n",
|
||||
" label,\n",
|
||||
" [(m.start(), m.end() - 1) for m in re.finditer(label, txt)]\n",
|
||||
" ))\n",
|
||||
"\n",
|
||||
" return results"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 34,
|
||||
"id": "7cc3ad1f",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"[('program', [(14, 20), (291, 297), (468, 474), (516, 522), (533, 539)]),\n",
|
||||
" ('application', [(80, 90), (164, 174), (322, 332)]),\n",
|
||||
" ('applet', [(302, 307)]),\n",
|
||||
" ('compile', [(56, 62)])]"
|
||||
]
|
||||
},
|
||||
"execution_count": 34,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"terminology_lookup(text, dictionary)"
|
||||
]
|
||||
},
|
||||
{
|
||||
|
|
@ -161,7 +195,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"execution_count": 35,
|
||||
"id": "tribal-attention",
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
|
|
@ -205,7 +239,7 @@
|
|||
"IDE\n",
|
||||
",\n",
|
||||
"see\n",
|
||||
"Running\n",
|
||||
"run\n",
|
||||
"Tutorial\n",
|
||||
"Examples\n",
|
||||
"in\n",
|
||||
|
|
@ -218,7 +252,7 @@
|
|||
"work\n",
|
||||
"for\n",
|
||||
"all\n",
|
||||
"swing\n",
|
||||
"Swing\n",
|
||||
"program\n",
|
||||
"—\n",
|
||||
"applet\n",
|
||||
|
|
@ -232,7 +266,7 @@
|
|||
"be\n",
|
||||
"the\n",
|
||||
"step\n",
|
||||
"-PRON-\n",
|
||||
"you\n",
|
||||
"need\n",
|
||||
"to\n",
|
||||
"follow\n",
|
||||
|
|
@ -248,7 +282,7 @@
|
|||
"platform\n",
|
||||
",\n",
|
||||
"if\n",
|
||||
"-PRON-\n",
|
||||
"you\n",
|
||||
"have\n",
|
||||
"not\n",
|
||||
"already\n",
|
||||
|
|
@ -260,7 +294,7 @@
|
|||
"program\n",
|
||||
"that\n",
|
||||
"use\n",
|
||||
"Swing\n",
|
||||
"swing\n",
|
||||
"component\n",
|
||||
".\n",
|
||||
"compile\n",
|
||||
|
|
@ -302,7 +336,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"execution_count": 36,
|
||||
"id": "surgical-demonstration",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
@ -337,7 +371,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"execution_count": 37,
|
||||
"id": "superb-butterfly",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
@ -356,7 +390,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 7,
|
||||
"execution_count": 38,
|
||||
"id": "acting-tolerance",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
@ -374,7 +408,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 8,
|
||||
"execution_count": 39,
|
||||
"id": "eight-redhead",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
@ -393,7 +427,7 @@
|
|||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 9,
|
||||
"execution_count": 40,
|
||||
"id": "monetary-mambo",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
|
|
@ -422,7 +456,7 @@
|
|||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.8.10"
|
||||
"version": "3.7.9"
|
||||
},
|
||||
"subtitle": "3. Terminologia",
|
||||
"title": "Komputerowe wspomaganie tłumaczenia",
|
||||
|
|
|
|||
Loading…
Reference in New Issue