Preprocessing text for each analyis type

This commit is contained in:
Henry Dowd
2025-11-21 18:31:23 +00:00
parent c2e88b26ca
commit a0e88c1525

View File

@@ -1,5 +1,37 @@
{
"cells": [
{
"metadata": {},
"cell_type": "markdown",
"source": "Import Cell\n",
"id": "dd72d1539056a64"
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-11-21T17:01:35.974978Z",
"start_time": "2025-11-21T17:01:34.412508Z"
}
},
"cell_type": "code",
"source": [
"import token\n",
"import spacy\n",
"from spacy import displacy\n",
"from IPython.display import display, HTML\n",
"\n",
"nlp = spacy.load(\"en_core_web_md\") # Medium size model\n",
"\n",
"test_sentences = [\n",
" \"The cat sat on the mat.\",\n",
" \"On the mat, the cat was sitting.\",\n",
" \"A completely different sentence about something else.\"\n",
"]"
],
"id": "12579bf734bb1a92",
"outputs": [],
"execution_count": 21
},
{
"metadata": {},
"cell_type": "markdown",
@@ -15,16 +47,6 @@
},
"cell_type": "code",
"source": [
"import token\n",
"import spacy\n",
"\n",
"nlp = spacy.load(\"en_core_web_md\") # Can swap for large model if required\n",
"\n",
"test_sentences = [\n",
" \"The cat sat on the mat.\",\n",
" \"On the mat, the cat was sitting.\",\n",
" \"A completely different sentence about something else.\"\n",
"]\n",
"\n",
"for sent in test_sentences:\n",
" doc = nlp(sent)\n",
@@ -55,65 +77,98 @@
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-11-20T19:53:11.868566Z",
"start_time": "2025-11-20T19:53:11.861295Z"
"end_time": "2025-11-21T16:32:45.216663Z",
"start_time": "2025-11-21T16:32:42.601290Z"
}
},
"cell_type": "code",
"source": [
"import spacy\n",
"import token\n",
"\n",
"nlp = spacy.load(\"en_core_web_md\")\n",
"\n",
"test_sentences = [\n",
" \"The cat sat on the mat.\",\n",
" \"On the mat, the cat was sitting.\",\n",
" \"A completely different sentence about something else.\"\n",
"]\n",
"\n",
"class TextPreprocessor:\n",
" def __init__(self):\n",
" self.nlp = spacy.load(\"en_core_web_md\")\n",
"\n",
" def direct_detection(self, text):\n",
" \"\"\"For direct copy detection\"\"\"\n",
" #Keep punctuation\n",
" return text.lower().strip()\n",
"\n",
" def semantic_analysis(self, text):\n",
" \"\"\"Semantic Similarity\"\"\"\n",
" doc = self.nlp(text)\n",
" tokens = []\n",
" for token in doc:\n",
" if (not token.is_punct and not token.is_space and token.is_alpha and token.is_stop and len(token.lemma_) > 1): #Remove single char tokens\n",
" tokens.append(token.lemma_.lower())\n",
" return \" \".join(tokens)\n",
" @staticmethod\n",
" def direct_detection(text):\n",
" \"\"\"For direct copy detection\"\"\"\n",
" #Keep punctuation\n",
" return text.lower().strip()\n",
"\n",
" def semantic_analysis(self, text):\n",
" \"\"\"Semantic Similarity\"\"\"\n",
" doc = self.nlp(text)\n",
" processed_tokens = []\n",
" # Remove stopwords, punctuation\n",
" for token in doc:\n",
" if not token.is_punct and not token.is_space and token.is_alpha and not token.is_stop:\n",
" processed_tokens.append(token.lemma_.lower())\n",
" return \" \".join(processed_tokens)\n",
"\n",
" def syntactic_analysis(self, text):\n",
" \"\"\"Syntactic Similarity\"\"\"\n",
" doc = self.nlp(text)\n",
" processed_tokens = []\n",
"\n",
" # Normalize content words\n",
" for token in doc:\n",
" if token.is_space:\n",
" continue\n",
" elif token.is_punct:\n",
" processed_tokens.append(token.text) # Keep punctuation\n",
" elif token.is_stop:\n",
" processed_tokens.append(token.lemma_.lower()) # Normalize stopwords\n",
" else:\n",
" processed_tokens.append(token.lemma_.lower()) # Normalize content words\n",
" return \" \".join(processed_tokens)\n",
"\n",
"\n",
"preprocessor = TextPreprocessor()\n",
"\n",
"processed_direct = []\n",
"processed_semantic = []\n",
"processed_syntactic = []\n",
"\n",
"for sentence in test_sentences:\n",
" processed_direct[iter] = preprocessor.semantic_analysis(sentence)\n",
"#print(preprocessor.syntactic_analysis(\"A completely different sentence about something else.\"))\n",
"\n",
"\n",
"for sent in test_sentences:\n",
" print(f\"Original Sentence: {sent}\")\n",
" print(\"---\")\n",
" print(f\"Preprocessed Sentence: {preprocess_semantic(sent)}\")\n",
" print(\"-\" * 50)"
" print(\"--- Semantic Analysis ---\")\n",
" print(f\"Preprocessed Sentence: {preprocessor.semantic_analysis(sent)}\")\n",
" print(\"--- Syntactic Analysis ---\")\n",
" print(f\"Preprocessed Sentence: {preprocessor.syntactic_analysis(sent)}\")\n",
" print(\"-\" * 50)"
],
"id": "5e488a878a5cfccb",
"outputs": [
{
"ename": "IndentationError",
"evalue": "expected an indented block after 'if' statement on line 26 (400725648.py, line 31)",
"output_type": "error",
"traceback": [
" \u001B[36mCell\u001B[39m\u001B[36m \u001B[39m\u001B[32mIn[19]\u001B[39m\u001B[32m, line 31\u001B[39m\n\u001B[31m \u001B[39m\u001B[31mfor sent in test_sentences:\u001B[39m\n ^\n\u001B[31mIndentationError\u001B[39m\u001B[31m:\u001B[39m expected an indented block after 'if' statement on line 26\n"
"name": "stdout",
"output_type": "stream",
"text": [
"Original Sentence: The cat sat on the mat.\n",
"--- Semantic Analysis ---\n",
"Preprocessed Sentence: cat sit mat\n",
"--- Syntactic Analysis ---\n",
"Preprocessed Sentence: the cat sit on the mat .\n",
"--------------------------------------------------\n",
"Original Sentence: On the mat, the cat was sitting.\n",
"--- Semantic Analysis ---\n",
"Preprocessed Sentence: mat cat sit\n",
"--- Syntactic Analysis ---\n",
"Preprocessed Sentence: on the mat , the cat be sit .\n",
"--------------------------------------------------\n",
"Original Sentence: A completely different sentence about something else.\n",
"--- Semantic Analysis ---\n",
"Preprocessed Sentence: completely different sentence\n",
"--- Syntactic Analysis ---\n",
"Preprocessed Sentence: a completely different sentence about something else .\n",
"--------------------------------------------------\n"
]
}
],
"execution_count": 19
"execution_count": 17
},
{
"metadata": {
@@ -124,9 +179,6 @@
},
"cell_type": "code",
"source": [
"import spacy\n",
"\n",
"nlp = spacy.load(\"en_core_web_md\")\n",
"\n",
"def extract_parse_tree(text):\n",
" doc = nlp(text)\n",
@@ -140,12 +192,6 @@
"\n",
" return doc\n",
"\n",
"test_sentences = [\n",
" \"The cat sat on the mat.\",\n",
" \"On the mat, the cat was sitting.\",\n",
" \"A completely different sentence about something else.\"\n",
"]\n",
"\n",
"for sentence in test_sentences:\n",
" doc = extract_parse_tree(sentence)\n",
" print(\"\\n\" + \"=\"*60 + \"\\n\")"
@@ -206,34 +252,36 @@
],
"execution_count": 15
},
{
"metadata": {},
"cell_type": "markdown",
"source": "***USE NetworkX",
"id": "5b5c8742d7c4c4c5"
},
{
"metadata": {
"ExecuteTime": {
"end_time": "2025-11-20T15:46:08.461059Z",
"start_time": "2025-11-20T15:45:47.529073Z"
"end_time": "2025-11-21T18:20:09.575176Z",
"start_time": "2025-11-21T18:20:09.465504Z"
}
},
"cell_type": "code",
"source": [
"import spacy\n",
"from spacy import displacy\n",
"from IPython.display import display, HTML\n",
"\n",
"nlp = spacy.load(\"en_core_web_md\")\n",
"\n",
"test_sentences = [\n",
" \"The cat sat on the mat.\",\n",
" \"On the mat, the cat was sitting.\",\n",
" \"A completely different sentence about something else.\"\n",
"]\n",
"\n",
"def visualize_parse_tree(text):\n",
" doc = nlp(text)\n",
" html = displacy.render(doc, style=\"dep\", jupyter=False, options={\"distance\": 100})\n",
" display(HTML(html))\n",
"\n",
"\n",
"\n",
"for sentence in test_sentences:\n",
" print(f\"Sentence: {sentence}\")\n",
" print(\"---\")\n",
" processed_sentence = preprocessor.syntactic_analysis(sentence)\n",
" print(f\"Processed Sentence: \" + processed_sentence)\n",
" visualize_parse_tree(processed_sentence)\n",
" visualize_parse_tree(sentence)"
],
"id": "e413238c1af12f62",
@@ -242,7 +290,9 @@
"name": "stdout",
"output_type": "stream",
"text": [
"Sentence: The cat sat on the mat.\n"
"Sentence: The cat sat on the mat.\n",
"---\n",
"Processed Sentence: the cat sit on the mat .\n"
]
},
{
@@ -251,7 +301,92 @@
"<IPython.core.display.HTML object>"
],
"text/html": [
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xml:lang=\"en\" id=\"30acd41e2fa8417a92c8204d90501047-0\" class=\"displacy\" width=\"650\" height=\"237.0\" direction=\"ltr\" style=\"max-width: none; height: 237.0px; color: #000000; background: #ffffff; font-family: Arial; direction: ltr\">\n",
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xml:lang=\"en\" id=\"cbdcc1a7b2c3434da049b33ce22ba9dc-0\" class=\"displacy\" width=\"650\" height=\"237.0\" direction=\"ltr\" style=\"max-width: none; height: 237.0px; color: #000000; background: #ffffff; font-family: Arial; direction: ltr\">\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
" <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"50\">the</tspan>\n",
" <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"50\">DET</tspan>\n",
"</text>\n",
"\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
" <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"150\">cat</tspan>\n",
" <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"150\">NOUN</tspan>\n",
"</text>\n",
"\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
" <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"250\">sit</tspan>\n",
" <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"250\">VERB</tspan>\n",
"</text>\n",
"\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
" <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"350\">on</tspan>\n",
" <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"350\">ADP</tspan>\n",
"</text>\n",
"\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
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"\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
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"\n",
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" </text>\n",
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"</g>\n",
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" </text>\n",
" <path class=\"displacy-arrowhead\" d=\"M170,104.0 L162,92.0 178,92.0\" fill=\"currentColor\"/>\n",
"</g>\n",
"\n",
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" </text>\n",
" <path class=\"displacy-arrowhead\" d=\"M345.0,104.0 L353.0,92.0 337.0,92.0\" fill=\"currentColor\"/>\n",
"</g>\n",
"\n",
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" </text>\n",
" <path class=\"displacy-arrowhead\" d=\"M470,104.0 L462,92.0 478,92.0\" fill=\"currentColor\"/>\n",
"</g>\n",
"\n",
"<g class=\"displacy-arrow\">\n",
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" </text>\n",
" <path class=\"displacy-arrowhead\" d=\"M550.0,104.0 L558.0,92.0 542.0,92.0\" fill=\"currentColor\"/>\n",
"</g>\n",
"</svg>"
]
},
"metadata": {},
"output_type": "display_data",
"jetTransient": {
"display_id": null
}
},
{
"data": {
"text/plain": [
"<IPython.core.display.HTML object>"
],
"text/html": [
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" xml:lang=\"en\" id=\"03663f6b8c874937b96eb1c0bf766ed5-0\" class=\"displacy\" width=\"650\" height=\"237.0\" direction=\"ltr\" style=\"max-width: none; height: 237.0px; color: #000000; background: #ffffff; font-family: Arial; direction: ltr\">\n",
"<text class=\"displacy-token\" fill=\"currentColor\" text-anchor=\"middle\" y=\"147.0\">\n",
" <tspan class=\"displacy-word\" fill=\"currentColor\" x=\"50\">The</tspan>\n",
" <tspan class=\"displacy-tag\" dy=\"2em\" fill=\"currentColor\" x=\"50\">DET</tspan>\n",
@@ -283,41 +418,41 @@
"</text>\n",
"\n",
"<g class=\"displacy-arrow\">\n",
" <path class=\"displacy-arc\" id=\"arrow-30acd41e2fa8417a92c8204d90501047-0-0\" stroke-width=\"2px\" d=\"M70,102.0 C70,52.0 145.0,52.0 145.0,102.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
" <path class=\"displacy-arc\" id=\"arrow-03663f6b8c874937b96eb1c0bf766ed5-0-0\" stroke-width=\"2px\" d=\"M70,102.0 C70,52.0 145.0,52.0 145.0,102.0\" fill=\"none\" stroke=\"currentColor\"/>\n",
" <text dy=\"1.25em\" style=\"font-size: 0.8em; letter-spacing: 1px\">\n",
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" <textPath xlink:href=\"#arrow-03663f6b8c874937b96eb1c0bf766ed5-0-0\" class=\"displacy-label\" startOffset=\"50%\" side=\"left\" fill=\"currentColor\" text-anchor=\"middle\">det</textPath>\n",
" </text>\n",
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"</g>\n",
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" </text>\n",
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"</g>\n",
"\n",
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" </text>\n",
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"</g>\n",
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" </text>\n",
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"</g>\n",
"\n",
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@@ -334,7 +469,9 @@
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"Sentence: On the mat, the cat was sitting.\n",
"---\n",
"Processed Sentence: on the mat , the cat be sit .\n"
]
},
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@@ -343,7 +480,105 @@
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{
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@@ -380,49 +615,49 @@
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@@ -439,7 +674,9 @@
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