ormatting changes for notebooks
This commit is contained in:
Henry Dowd
@@ -77,8 +77,8 @@
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-21T16:32:45.216663Z",
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"start_time": "2025-11-21T16:32:42.601290Z"
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"end_time": "2025-11-21T23:26:23.172796Z",
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"start_time": "2025-11-21T23:26:21.541542Z"
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}
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},
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"cell_type": "code",
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@@ -129,17 +129,29 @@
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"processed_syntactic = []\n",
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"\n",
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"for sentence in test_sentences:\n",
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" processed_direct[iter] = preprocessor.semantic_analysis(sentence)\n",
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"#print(preprocessor.syntactic_analysis(\"A completely different sentence about something else.\"))\n",
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" print(\"-\" * 50)\n",
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" print(f\"Sentence: {sentence}\")\n",
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" direct = preprocessor.direct_detection(sentence)\n",
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" processed_direct.append(direct)\n",
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" print(\"--- Direct Sentence ---\")\n",
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" print(f\"{direct}\")\n",
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" semantic = preprocessor.semantic_analysis(sentence)\n",
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" processed_semantic.append(semantic)\n",
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" print(\"--- Semantic Sentence ---\")\n",
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" print(f\"{semantic}\")\n",
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" syntactic = preprocessor.syntactic_analysis(sentence)\n",
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" processed_syntactic.append(syntactic)\n",
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" print(\"--- Syntactic Sentence ---\")\n",
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" print(f\"{syntactic}\")\n",
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"\n",
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"\n",
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"for sent in test_sentences:\n",
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" print(f\"Original Sentence: {sent}\")\n",
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" print(\"--- Semantic Analysis ---\")\n",
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" print(f\"Preprocessed Sentence: {preprocessor.semantic_analysis(sent)}\")\n",
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" print(\"--- Syntactic Analysis ---\")\n",
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" print(f\"Preprocessed Sentence: {preprocessor.syntactic_analysis(sent)}\")\n",
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" print(\"-\" * 50)"
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"print(\"-\" * 50)\n",
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"#for sent in test_sentences:\n",
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"# print(f\"Original Sentence: {sent}\")\n",
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"# print(\"--- Semantic Analysis ---\")\n",
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"# print(f\"Preprocessed Sentence: {preprocessor.semantic_analysis(sent)}\")\n",
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"# print(\"--- Syntactic Analysis ---\")\n",
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"# print(f\"Preprocessed Sentence: {preprocessor.syntactic_analysis(sent)}\")\n",
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"# print(\"-\" * 50)"
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],
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"id": "5e488a878a5cfccb",
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"outputs": [
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@@ -147,34 +159,41 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Original Sentence: The cat sat on the mat.\n",
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"--- Semantic Analysis ---\n",
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"Preprocessed Sentence: cat sit mat\n",
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"--- Syntactic Analysis ---\n",
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"Preprocessed Sentence: the cat sit on the mat .\n",
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"--------------------------------------------------\n",
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"Original Sentence: On the mat, the cat was sitting.\n",
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"--- Semantic Analysis ---\n",
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"Preprocessed Sentence: mat cat sit\n",
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"--- Syntactic Analysis ---\n",
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"Preprocessed Sentence: on the mat , the cat be sit .\n",
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"Sentence: The cat sat on the mat.\n",
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"--- Direct Sentence ---\n",
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"the cat sat on the mat.\n",
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"--- Semantic Sentence ---\n",
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"cat sit mat\n",
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"--- Syntactic Sentence ---\n",
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"the cat sit on the mat .\n",
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"--------------------------------------------------\n",
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"Original Sentence: A completely different sentence about something else.\n",
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"--- Semantic Analysis ---\n",
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"Preprocessed Sentence: completely different sentence\n",
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"--- Syntactic Analysis ---\n",
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"Preprocessed Sentence: a completely different sentence about something else .\n",
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"Sentence: On the mat, the cat was sitting.\n",
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"--- Direct Sentence ---\n",
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"on the mat, the cat was sitting.\n",
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"--- Semantic Sentence ---\n",
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"mat cat sit\n",
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"--- Syntactic Sentence ---\n",
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"on the mat , the cat be sit .\n",
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"--------------------------------------------------\n",
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"Sentence: A completely different sentence about something else.\n",
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"--- Direct Sentence ---\n",
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"a completely different sentence about something else.\n",
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"--- Semantic Sentence ---\n",
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"completely different sentence\n",
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"--- Syntactic Sentence ---\n",
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"a completely different sentence about something else .\n",
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"--------------------------------------------------\n"
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]
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}
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],
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"execution_count": 17
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"execution_count": 37
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},
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-20T15:51:42.074798Z",
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"start_time": "2025-11-20T15:51:42.050593Z"
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"end_time": "2025-11-21T23:39:48.443022Z",
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"start_time": "2025-11-21T23:39:48.411766Z"
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}
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},
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"cell_type": "code",
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@@ -192,7 +211,7 @@
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"\n",
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" return doc\n",
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"\n",
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"for sentence in test_sentences:\n",
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"for sentence in processed_syntactic:\n",
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" doc = extract_parse_tree(sentence)\n",
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" print(\"\\n\" + \"=\"*60 + \"\\n\")"
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],
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@@ -202,44 +221,44 @@
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Sentence: The cat sat on the mat.\n",
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"Sentence: the cat sit on the mat .\n",
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"\n",
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"Dependenct Parse Tree:\n",
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"--------------------------------------------------\n",
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"The det cat []\n",
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"cat nsubj sat ['The']\n",
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"sat ROOT sat ['cat', 'on', '.']\n",
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"on prep sat ['mat']\n",
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"the det cat []\n",
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"cat nsubj sit ['the']\n",
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"sit ROOT sit ['cat', 'on', '.']\n",
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"on prep sit ['mat']\n",
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"the det mat []\n",
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"mat pobj on ['the']\n",
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". punct sat []\n",
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". punct sit []\n",
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"\n",
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"============================================================\n",
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"\n",
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"Sentence: On the mat, the cat was sitting.\n",
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"Sentence: on the mat , the cat be sit .\n",
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"\n",
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"Dependenct Parse Tree:\n",
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"--------------------------------------------------\n",
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"On prep sitting ['mat']\n",
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"on prep sit ['mat']\n",
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"the det mat []\n",
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"mat pobj On ['the']\n",
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", punct sitting []\n",
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"mat pobj on ['the']\n",
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", punct sit []\n",
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"the det cat []\n",
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"cat nsubj sitting ['the']\n",
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"was aux sitting []\n",
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"sitting ROOT sitting ['On', ',', 'cat', 'was', '.']\n",
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". punct sitting []\n",
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"cat nsubj sit ['the']\n",
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"be aux sit []\n",
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"sit ROOT sit ['on', ',', 'cat', 'be', '.']\n",
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". punct sit []\n",
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"\n",
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"============================================================\n",
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"\n",
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"Sentence: A completely different sentence about something else.\n",
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"Sentence: a completely different sentence about something else .\n",
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"\n",
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"Dependenct Parse Tree:\n",
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"--------------------------------------------------\n",
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"A det sentence []\n",
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"a det sentence []\n",
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"completely advmod different []\n",
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"different amod sentence ['completely']\n",
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"sentence ROOT sentence ['A', 'different', 'about', '.']\n",
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"sentence ROOT sentence ['a', 'different', 'about', '.']\n",
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"about prep sentence ['something']\n",
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"something pobj about ['else']\n",
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"else advmod something []\n",
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@@ -250,7 +269,7 @@
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]
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}
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],
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"execution_count": 15
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"execution_count": 39
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},
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{
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"metadata": {},
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@@ -1,5 +1,21 @@
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{
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"cells": [
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-22T11:40:21.711998Z",
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"start_time": "2025-11-22T11:40:20.129376Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import spacy\n",
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"nlp = spacy.load(\"en_core_web_md\") # Medium model"
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],
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"id": "1638b7b97e3bd6f",
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"outputs": [],
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"execution_count": 11
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},
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{
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"metadata": {},
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"cell_type": "markdown",
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@@ -9,19 +25,16 @@
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{
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"metadata": {
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"ExecuteTime": {
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"end_time": "2025-11-18T23:28:55.563335Z",
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"start_time": "2025-11-18T23:28:53.763429Z"
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"end_time": "2025-11-22T11:47:39.286432Z",
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"start_time": "2025-11-22T11:47:39.271377Z"
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}
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},
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"cell_type": "code",
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"source": [
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"import import_ipynb\n",
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"#from notebooks. import *\n",
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"def test_word_vectors(word):\n",
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" print(word, nlp.vocab[word].vector.shape)\n",
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"\n",
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"import spacy\n",
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"nlp = spacy.load(\"en_core_web_md\")\n",
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"\n",
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"words = [\"cat\", \"dog\", \"feline\", \"vehicle\", \"car\"]\n",
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"words = [\"cat\", \"dog\", \"feline\", \"feral\", \"vehicle\", \"car\"]\n",
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"# Test work similarities\n",
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"for word1 in words:\n",
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" for word2 in words:\n",
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@@ -39,28 +52,38 @@
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"text": [
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"cat - dog: 1.000\n",
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"cat - feline: 0.363\n",
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"cat - feral: 0.483\n",
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"cat - vehicle: 0.078\n",
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"cat - car: 0.193\n",
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"dog - cat: 1.000\n",
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"dog - feline: 0.363\n",
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"dog - feral: 0.483\n",
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"dog - vehicle: 0.078\n",
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"dog - car: 0.193\n",
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"feline - cat: 0.363\n",
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"feline - dog: 0.363\n",
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"feline - feral: 0.412\n",
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"feline - vehicle: 0.180\n",
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"feline - car: 0.050\n",
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"feral - cat: 0.483\n",
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"feral - dog: 0.483\n",
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"feral - feline: 0.412\n",
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"feral - vehicle: 0.175\n",
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"feral - car: 0.161\n",
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"vehicle - cat: 0.078\n",
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"vehicle - dog: 0.078\n",
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"vehicle - feline: 0.180\n",
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"vehicle - feral: 0.175\n",
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"vehicle - car: 0.205\n",
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"car - cat: 0.193\n",
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"car - dog: 0.193\n",
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"car - feline: 0.050\n",
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"car - feral: 0.161\n",
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"car - vehicle: 0.205\n"
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]
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}
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],
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"execution_count": 1
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"execution_count": 15
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},
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{
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"metadata": {},
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