forked from bfijalkowski/KWT-2024
[2024-04-13] labs 1,2,3
This commit is contained in:
Patryk Bartkowiak
parent
71ca3b66ed
commit
870b673fac
223
lab/lab_01.ipynb
223
lab/lab_01.ipynb
@ -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": 191,
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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": 192,
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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": 193,
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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": 193,
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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": 194,
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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": 195,
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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": 195,
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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": 196,
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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": 196,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -213,13 +213,37 @@
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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": 197,
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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 preprocess(sentence):\n",
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" return sentence.lower()\n",
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"\n",
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"def tm_lookup(sentence):\n",
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" return ''"
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" return [entry[1] for entry in translation_memory if preprocess(entry[0]) == preprocess(sentence)]"
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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": 198,
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"id": "7baee10b",
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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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"['Press the ENTER button', 'Press the ENTER key']"
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]
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},
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"execution_count": 198,
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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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"tm_lookup('Wciśnij przycisk ENTER')"
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]
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},
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{
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@ -232,17 +256,17 @@
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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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"execution_count": 199,
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"id": "severe-alloy",
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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": 199,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -261,13 +285,40 @@
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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": 200,
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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 preprocess(s):\n",
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" translator = str.maketrans('', '', string.punctuation)\n",
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" return s.translate(translator).lower()\n",
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"\n",
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"def tm_lookup(sentence):\n",
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" return ''"
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" return [entry[1] for entry in translation_memory if preprocess(entry[0]) == preprocess(sentence)]"
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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": 201,
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"id": "c03c6709",
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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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"['Press the ENTER button', 'Press the ENTER key']"
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]
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},
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"execution_count": 201,
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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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"tm_lookup('Wciśnij przycisk [ENTER]')"
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]
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},
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{
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@ -280,17 +331,17 @@
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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": 202,
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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": 202,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -317,13 +368,43 @@
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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": 203,
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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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"def compare_sentences(l1, l2):\n",
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" return sum([1 for i, j in zip(l1.split(), l2.split()) if i != j]) <= 1\n",
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"\n",
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"import string\n",
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"\n",
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"def preprocess(s):\n",
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" translator = str.maketrans('', '', string.punctuation)\n",
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" return s.translate(translator).lower()\n",
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"\n",
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"def tm_lookup(sentence):\n",
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" return ''"
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" return [entry[1] for entry in translation_memory if compare_sentences(preprocess(entry[0]), preprocess(sentence))]"
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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": 204,
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"id": "6264b722",
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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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"['System restart required']"
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]
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},
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"execution_count": 204,
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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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"tm_lookup('Wymagane ponowne uruchomienie maszyny')"
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]
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},
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{
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@ -344,7 +425,7 @@
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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": 205,
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"id": "humanitarian-wrong",
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"metadata": {},
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"outputs": [],
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@ -362,7 +443,7 @@
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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": 206,
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"id": "located-perception",
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"metadata": {},
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"outputs": [],
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@ -374,7 +455,7 @@
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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": 207,
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"id": "advised-casting",
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"metadata": {},
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"outputs": [
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@ -384,7 +465,7 @@
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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": 207,
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"metadata": {},
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"output_type": "execute_result"
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}
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@ -406,7 +487,7 @@
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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: Jeżeli implementacja wygląda tak jak powyżej, złożoność to `O(n*m)`, ponieważ dla każdego słowa iteracyjnie przechodzimy przez cały nasz słownik i szukamy odpowiednika"
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]
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},
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{
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@ -419,13 +500,56 @@
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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": 208,
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"id": "aca5d340",
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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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"[('przycisk', 'button')]"
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]
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},
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"execution_count": 208,
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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('Każda Drukarka posiada przycisk wznowienia drukowania')"
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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": 209,
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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 glossary_lookup(sentence):\n",
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" return ''"
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" sentence_words = [word.lower() for word in sentence.split()]\n",
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" return [entry for entry in glossary if entry[0] in sentence_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": 210,
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"id": "716bbbe9",
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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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"[('przycisk', 'button'), ('drukarka', 'printer')]"
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]
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},
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"execution_count": 210,
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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('Każda drukarka posiada przycisk wznowienia drukowania')"
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]
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},
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{
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@ -438,13 +562,50 @@
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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": 211,
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"id": "32dec661",
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"metadata": {},
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"outputs": [],
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"source": [
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"glossary = [('komputer', 'computer'), ('przycisk', 'button'), ('drukarka', 'printer')]\n",
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"glossary = {\n",
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" 'komputer': 'computer',\n",
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" 'przycisk': 'button',\n",
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" 'drukarka': 'printer'\n",
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"}"
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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": 212,
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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 glossary_lookup(sentence):\n",
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" return ''"
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" sentence_words = [word.lower() for word in sentence.split() if word.lower() in glossary]\n",
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" return [(word, glossary[word]) for word in sentence_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": 213,
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"id": "d1e991c6",
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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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"[('drukarka', 'printer'), ('przycisk', 'button')]"
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]
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},
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"execution_count": 213,
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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('Każda drukarka posiada przycisk wznowienia drukowania')"
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]
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}
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],
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@ -467,7 +628,7 @@
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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": "3.10.14"
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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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104
lab/lab_02.ipynb
104
lab/lab_02.ipynb
@ -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": 17,
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"id": "confident-prison",
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"metadata": {},
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"outputs": [],
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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": 18,
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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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" return []"
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" # Wyniki dopasowania ICE\n",
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" ice_matches = []\n",
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"\n",
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" # Iterujemy przez pamięć tłumaczeń, pomijając pierwszy i ostatni element dla bezpieczeństwa kontekstowego\n",
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" for index in range(1, len(translation_memory) - 1):\n",
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" # Pobieramy obecne, poprzednie i następne zdania z TM\n",
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" prev_tm_sentence, _ = translation_memory[index - 1]\n",
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" current_tm_sentence, current_tm_translation = translation_memory[index]\n",
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" next_tm_sentence, _ = translation_memory[index + 1]\n",
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"\n",
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" # Sprawdzamy, czy wszystkie trzy zdania zgadzają się z odpowiednikami w TM\n",
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" if (prev_tm_sentence == prev_sentence and current_tm_sentence == current_sentence and next_tm_sentence == next_sentence):\n",
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" ice_matches.append(current_tm_translation)\n",
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"\n",
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" return ice_matches"
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]
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},
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{
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@ -119,7 +133,7 @@
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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": 19,
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"id": "fourth-pillow",
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"metadata": {},
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"outputs": [],
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@ -141,7 +155,11 @@
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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, ponieważ w tej funkcji interesuje nas tylko długość zdania, tzn. drugi warunek nie będzie spełniony\n",
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"\n",
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"Przykład: `kot != bok`, a dla tej funkcji zwróci 0\n",
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"\n",
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"Spełnione warunki: 1, 3, 4"
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]
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},
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{
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@ -154,7 +172,7 @@
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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": 20,
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"id": "continued-christopher",
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"metadata": {},
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"outputs": [],
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@ -179,7 +197,40 @@
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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: Tak, spełnia wszystkie warunki\n",
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"\n",
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"Sprawdzenie dla warunku 4"
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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": 29,
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"id": "349a3547",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"True\n",
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"True\n",
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"True\n",
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||||
"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",
|
||||
|
||||
351
lab/lab_03.ipynb
351
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",
|
||||
|
||||
Loading…
Reference in New Issue
Block a user