mirror of
https://github.com/gsi-upm/sitc
synced 2025-08-24 02:22:21 +00:00
Included installation of nltk
This commit is contained in:
cif2cif
@@ -61,7 +61,7 @@
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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": null,
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"metadata": {
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"collapsed": false
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},
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@@ -109,19 +109,11 @@
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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": null,
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"metadata": {
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"collapsed": false
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},
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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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"[('I', 'PRON'), ('purchased', 'VERB'), ('this', 'DET'), ('Dell', 'NOUN'), ('monitor', 'NOUN'), ('because', 'ADP'), ('of', 'ADP'), ('budgetary', 'ADJ'), ('concerns', 'NOUN'), ('.', '.'), ('This', 'DET'), ('item', 'NOUN'), ('was', 'VERB'), ('the', 'DET'), ('most', 'ADV'), ('inexpensive', 'ADJ'), ('17', 'NUM'), ('inch', 'NOUN'), ('Apple', 'NOUN'), ('monitor', 'NOUN'), ('available', 'ADJ'), ('to', 'PRT'), ('me', 'PRON'), ('at', 'ADP'), ('the', 'DET'), ('time', 'NOUN'), ('I', 'PRON'), ('made', 'VERB'), ('the', 'DET'), ('purchase', 'NOUN'), ('.', '.'), ('My', 'PRON'), ('overall', 'ADJ'), ('experience', 'NOUN'), ('with', 'ADP'), ('this', 'DET'), ('monitor', 'NOUN'), ('was', 'VERB'), ('very', 'ADV'), ('poor', 'ADJ'), ('.', '.'), ('When', 'ADV'), ('the', 'DET'), ('screen', 'NOUN'), ('was', 'VERB'), (\"n't\", 'ADV'), ('contracting', 'VERB'), ('or', 'CONJ'), ('glitching', 'VERB'), ('the', 'DET'), ('overall', 'ADJ'), ('picture', 'NOUN'), ('quality', 'NOUN'), ('was', 'VERB'), ('poor', 'ADJ'), ('to', 'PRT'), ('fair', 'VERB'), ('.', '.'), ('I', 'PRON'), (\"'ve\", 'VERB'), ('viewed', 'VERB'), ('numerous', 'ADJ'), ('different', 'ADJ'), ('monitor', 'NOUN'), ('models', 'NOUN'), ('since', 'ADP'), ('I', 'PRON'), (\"'m\", 'VERB'), ('a', 'DET'), ('college', 'NOUN'), ('student', 'NOUN'), ('at', 'ADP'), ('UPM', 'NOUN'), ('in', 'ADP'), ('Madrid', 'NOUN'), ('and', 'CONJ'), ('this', 'DET'), ('particular', 'ADJ'), ('monitor', 'NOUN'), ('had', 'VERB'), ('as', 'ADP'), ('poor', 'ADJ'), ('of', 'ADP'), ('picture', 'NOUN'), ('quality', 'NOUN'), ('as', 'ADP'), ('any', 'DET'), ('I', 'PRON'), (\"'ve\", 'VERB'), ('seen', 'VERB'), ('.', '.')]\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from nltk import pos_tag, word_tokenize\n",
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"print (pos_tag(word_tokenize(review), tagset='universal'))"
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@@ -136,19 +128,11 @@
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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": null,
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"metadata": {
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"collapsed": false
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},
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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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"['I', 'purchase', 'Dell', 'monitor', 'because', 'of', 'budgetary', 'concern', 'item', 'be', 'most', 'inexpensive', '17', 'inch', 'Apple', 'monitor', 'available', 'me', 'at', 'time', 'I', 'make', 'purchase', 'My', 'overall', 'experience', 'with', 'monitor', 'be', 'very', 'poor', 'When', 'screen', 'be', \"n't\", 'contract', 'or', 'glitching', 'overall', 'picture', 'quality', 'be', 'poor', 'fair', 'I', \"'ve\", 'view', 'numerous', 'different', 'monitor', 'model', 'since', 'I', \"'m\", 'college', 'student', 'at', 'UPM', 'in', 'Madrid', 'and', 'particular', 'monitor', 'have', 'a', 'poor', 'of', 'picture', 'quality', 'a', 'I', \"'ve\", 'see']\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from nltk.stem import WordNetLemmatizer\n",
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"\n",
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@@ -177,110 +161,11 @@
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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": null,
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"metadata": {
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"collapsed": false
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},
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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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"(S\n",
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" I/PRP\n",
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" purchased/VBD\n",
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" this/DT\n",
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" (ORGANIZATION Dell/NNP)\n",
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" monitor/NN\n",
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" because/IN\n",
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" of/IN\n",
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" budgetary/JJ\n",
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" concerns/NNS\n",
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" ./.\n",
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" This/DT\n",
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" item/NN\n",
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" was/VBD\n",
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" the/DT\n",
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" most/RBS\n",
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" inexpensive/JJ\n",
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" 17/CD\n",
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" inch/NN\n",
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" Apple/NNP\n",
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" monitor/NN\n",
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" available/JJ\n",
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" to/TO\n",
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" me/PRP\n",
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" at/IN\n",
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" the/DT\n",
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" time/NN\n",
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" I/PRP\n",
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" made/VBD\n",
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" the/DT\n",
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" purchase/NN\n",
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" ./.\n",
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" My/PRP$\n",
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" overall/JJ\n",
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" experience/NN\n",
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" with/IN\n",
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" this/DT\n",
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" monitor/NN\n",
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" was/VBD\n",
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" very/RB\n",
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" poor/JJ\n",
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" ./.\n",
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" When/WRB\n",
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" the/DT\n",
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" screen/NN\n",
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" was/VBD\n",
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" n't/RB\n",
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" contracting/VBG\n",
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" or/CC\n",
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" glitching/VBG\n",
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" the/DT\n",
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" overall/JJ\n",
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" picture/NN\n",
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" quality/NN\n",
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" was/VBD\n",
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" poor/JJ\n",
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" to/TO\n",
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" fair/VB\n",
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" ./.\n",
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" I/PRP\n",
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" 've/VBP\n",
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" viewed/VBN\n",
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" numerous/JJ\n",
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" different/JJ\n",
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" monitor/NN\n",
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" models/NNS\n",
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" since/IN\n",
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" I/PRP\n",
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" 'm/VBP\n",
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" a/DT\n",
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" college/NN\n",
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" student/NN\n",
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" at/IN\n",
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" (ORGANIZATION UPM/NNP)\n",
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" in/IN\n",
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" (GPE Madrid/NNP)\n",
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" and/CC\n",
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" this/DT\n",
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" particular/JJ\n",
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" monitor/NN\n",
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" had/VBD\n",
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" as/IN\n",
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" poor/JJ\n",
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" of/IN\n",
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" picture/NN\n",
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" quality/NN\n",
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" as/IN\n",
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" any/DT\n",
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" I/PRP\n",
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" 've/VBP\n",
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" seen/VBN\n",
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" ./.)\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from nltk import ne_chunk, pos_tag, word_tokenize\n",
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"ne_tagged = ne_chunk(pos_tag(word_tokenize(review)), binary=False)\n",
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@@ -321,7 +206,7 @@
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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": null,
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"metadata": {
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"collapsed": false
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},
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@@ -344,90 +229,11 @@
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},
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{
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"cell_type": "code",
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"execution_count": 42,
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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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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"(S\n",
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" I/PRON\n",
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" purchased/VERB\n",
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" (NP this/DET Dell/NOUN monitor/NOUN)\n",
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" because/ADP\n",
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" of/ADP\n",
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" (NP budgetary/ADJ concerns/NOUN)\n",
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" ./.\n",
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" (NP This/DET item/NOUN)\n",
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" was/VERB\n",
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" (NP\n",
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" the/DET\n",
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" most/ADV\n",
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" inexpensive/ADJ\n",
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" 17/NUM\n",
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" inch/NOUN\n",
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" Apple/NOUN\n",
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" monitor/NOUN)\n",
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" available/ADJ\n",
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" to/PRT\n",
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" me/PRON\n",
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" at/ADP\n",
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" (NP the/DET time/NOUN)\n",
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" I/PRON\n",
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" made/VERB\n",
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" (NP the/DET purchase/NOUN)\n",
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" ./.\n",
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" (NP My/PRON overall/ADJ experience/NOUN)\n",
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" with/ADP\n",
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" (NP this/DET monitor/NOUN)\n",
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" was/VERB\n",
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" very/ADV\n",
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" poor/ADJ\n",
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" ./.\n",
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" When/ADV\n",
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" (NP the/DET screen/NOUN)\n",
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" was/VERB\n",
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" n't/ADV\n",
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" contracting/VERB\n",
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" or/CONJ\n",
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" glitching/VERB\n",
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" (NP the/DET overall/ADJ picture/NOUN quality/NOUN)\n",
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" was/VERB\n",
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" poor/ADJ\n",
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" to/PRT\n",
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" fair/VERB\n",
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" ./.\n",
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" I/PRON\n",
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" 've/VERB\n",
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" viewed/VERB\n",
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" (NP numerous/ADJ different/ADJ monitor/NOUN models/NOUN)\n",
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" since/ADP\n",
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" I/PRON\n",
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" 'm/VERB\n",
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" (NP a/DET college/NOUN student/NOUN)\n",
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" at/ADP\n",
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" (NP UPM/NOUN)\n",
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" in/ADP\n",
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" (NP Madrid/NOUN)\n",
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" and/CONJ\n",
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" (NP this/DET particular/ADJ monitor/NOUN)\n",
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" had/VERB\n",
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" as/ADP\n",
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" poor/ADJ\n",
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" of/ADP\n",
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" (NP picture/NOUN quality/NOUN)\n",
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" as/ADP\n",
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" any/DET\n",
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" I/PRON\n",
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" 've/VERB\n",
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" seen/VERB\n",
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" ./.)\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"from nltk.chunk.regexp import *\n",
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"pattern = \"\"\"NP: {<PRON><ADJ><NOUN>+} \n",
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@@ -451,37 +257,11 @@
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},
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{
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"cell_type": "code",
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"execution_count": 54,
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[Tree('NP', [('this', 'DET'), ('Dell', 'NOUN'), ('monitor', 'NOUN')]),\n",
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" Tree('NP', [('budgetary', 'ADJ'), ('concerns', 'NOUN')]),\n",
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" Tree('NP', [('This', 'DET'), ('item', 'NOUN')]),\n",
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" Tree('NP', [('the', 'DET'), ('most', 'ADV'), ('inexpensive', 'ADJ'), ('17', 'NUM'), ('inch', 'NOUN'), ('Apple', 'NOUN'), ('monitor', 'NOUN')]),\n",
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" Tree('NP', [('the', 'DET'), ('time', 'NOUN')]),\n",
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" Tree('NP', [('the', 'DET'), ('purchase', 'NOUN')]),\n",
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" Tree('NP', [('My', 'PRON'), ('overall', 'ADJ'), ('experience', 'NOUN')]),\n",
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" Tree('NP', [('this', 'DET'), ('monitor', 'NOUN')]),\n",
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" Tree('NP', [('the', 'DET'), ('screen', 'NOUN')]),\n",
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" Tree('NP', [('the', 'DET'), ('overall', 'ADJ'), ('picture', 'NOUN'), ('quality', 'NOUN')]),\n",
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" Tree('NP', [('numerous', 'ADJ'), ('different', 'ADJ'), ('monitor', 'NOUN'), ('models', 'NOUN')]),\n",
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" Tree('NP', [('a', 'DET'), ('college', 'NOUN'), ('student', 'NOUN')]),\n",
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" Tree('NP', [('UPM', 'NOUN')]),\n",
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" Tree('NP', [('Madrid', 'NOUN')]),\n",
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" Tree('NP', [('this', 'DET'), ('particular', 'ADJ'), ('monitor', 'NOUN')]),\n",
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" Tree('NP', [('picture', 'NOUN'), ('quality', 'NOUN')])]"
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]
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},
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"execution_count": 54,
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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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"outputs": [],
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"source": [
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"def extractTrees(parsed_tree, category='NP'):\n",
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" return list(parsed_tree.subtrees(filter=lambda x: x.label()==category))\n",
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@@ -491,37 +271,11 @@
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},
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{
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"cell_type": "code",
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"execution_count": 90,
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"execution_count": null,
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"metadata": {
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"collapsed": false
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"['this Dell monitor',\n",
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" 'budgetary concerns',\n",
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" 'This item',\n",
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" 'the most inexpensive 17 inch Apple monitor',\n",
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" 'the time',\n",
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" 'the purchase',\n",
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" 'My overall experience',\n",
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" 'this monitor',\n",
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" 'the screen',\n",
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" 'the overall picture quality',\n",
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" 'numerous different monitor models',\n",
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" 'a college student',\n",
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" 'UPM',\n",
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" 'Madrid',\n",
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" 'this particular monitor',\n",
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" 'picture quality']"
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]
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},
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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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],
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"outputs": [],
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"source": [
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"def extractStrings(parsed_tree, category='NP'):\n",
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" return [\" \".join(word for word, pos in vp.leaves()) for vp in extractTrees(parsed_tree, category)]\n",
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@@ -529,15 +283,6 @@
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"extractStrings(chunks_np)"
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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": null,
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"metadata": {
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"collapsed": true
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},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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@@ -587,7 +332,7 @@
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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": "3.5.1"
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"version": "3.5.2"
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}
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},
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"nbformat": 4,
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