Relation Extractor
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❖ NLP & Text Analysis

Entity Relation Extractor

v1.0 documentation

Extract typed relationships between entities using dependency parsing. Build knowledge graph triples: (Subject, Relation, Object).

URL inputFile inputText inputXLSX export
relation_extractor.py108 lines5 paramsPython 3.8+
Quick start
1

Install

terminal
pip install -r requirements.txt
2

Run

terminal
python relation_extractor.py --url https://example.com/post --output relations.xlsx
terminal
python relation_extractor.py --file article.txt --format json --output relations.json
3

Export

Add --output report.xlsx to save results as a spreadsheet.

Parameters
FlagDescription
--urlUrl
--fileFile
--textText
--formatFormat. Options: xlsx, json, csv
--outputOutput
help
python relation_extractor.py --help
Use cases
Content quality audit
Writer evaluation
Client deliverable

Run across all your blog posts to score quality. Sort by score in the XLSX export, then prioritize rewrites for the lowest-scoring pages.

Before publishing freelance content, run this tool to check quality signals. Use specific metrics as concrete feedback for writers.

Include the analysis in your SEO audit report. Clients appreciate data-backed recommendations over subjective opinions.

Dependencies

Requires: beautifulsoup4, pandas, requests, spacy. All included in requirements.txt.

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Get the full toolkit

AAIO Inc — aaioinc.com/tools/relation_extractor/