Run3 Extract PDF Content and Metadata

When to use this skill

• When you need to read the actual content of a PDF paper to determine its subject
• When PDF filenames are identifiers (like 2105.03431v1.pdf) rather than descriptive titles
• Before sorting PDFs into subject folders to ensure accuracy

How to extract PDF content

Using PyPDF2 or pdfplumber

import pdfplumber

def extract_pdf_content(pdf_path):
    with pdfplumber.open(pdf_path) as pdf:
        # Extract first page (usually contains title and abstract)
        first_page = pdf.pages[0]
        text = first_page.extract_text()
        
        # Also extract from next 1-2 pages for full abstract
        if len(pdf.pages) > 1:
            text += "\n" + pdf.pages[1].extract_text()
        
        return text

Key information to extract

1. Title: Usually at the top of page 1
2. Abstract: Contains subject keywords and main topic
3. Keywords section: Often explicitly labeled
4. Introduction: First paragraph usually summarizes the field

What to look for in content

• LLM: Keywords like "language model", "transformer", "neural network", "NLP", "large language model", "BERT", "GPT"
• Trapped ion and quantum computing: Keywords like "trapped ion", "quantum computer", "qubit", "quantum gate", "quantum algorithm"
• Black hole: Keywords like "black hole", "event horizon", "gravitational", "spacetime", "Hawking", "relativity"
• DNA: Keywords like "DNA", "genetics", "gene", "molecular biology", "sequence", "protein"
• Music history: Keywords like "music", "composer", "symphony", "historical", "musical"

Store extracted content for analysis

Save the extracted text to a temporary variable or file for subject classification matching.