NAP-Consistency-Checker: Local SEO NAP and Entity Validation

Type: Commercial | Domain: SEO, Local SEO
Hugging Face: syeedalireza/nap-consistency-checker

Validate NAP (Name, Address, Phone) consistency and entity alignment across pages and citation sources.

Author

Alireza Aminzadeh

• Hugging Face: syeedalireza
• LinkedIn: alirezaaminzadeh
• Email: alireza.aminzadeh@hotmail.com

Problem

Local SEO depends on consistent NAP across site and citations. Detecting variations and normalizing entities reduces confusion for users and search engines.

Approach

• Input: Text snippets or structured NAP fields (name, address, phone) from multiple sources.
• Output: Consistency flags (match/mismatch), normalized canonical form, optional entity resolution (same business or not).
• Models: Rule-based normalization (address/phone parsing) + optional transformer/NER for extracting NAP from raw text; embedding similarity for entity matching.

Tech Stack

Category	Tools
NLP	Hugging Face Transformers, sentence-transformers (optional)
Rules	regex, standard phone/address parsing
Data	pandas, NumPy

Setup

pip install -r requirements.txt

Usage

python inference.py --input data/citations.csv --reference data/reference_nap.csv --output output/consistency_report.csv

• normalize.py provides NAP normalization helpers (used by inference). No separate “build canonical” step; the reference is read from the reference CSV.

Project structure

09_nap-consistency-checker/
├── config.py
├── normalize.py       # NAP normalization helpers
├── inference.py      # Compare citations to reference NAP
├── requirements.txt
├── .env.example
├── data/
│   ├── reference_nap.csv   # Canonical NAP (one row: name, address, phone)
│   └── citations.csv       # Source, name, address, phone per citation
└── output/                 # consistency_report.csv

Data

• Sample data (included): data/reference_nap.csv (one row: name, address, phone), data/citations.csv (columns: source, name, address, phone). Output: name_match, address_match, phone_match, nap_consistent.

License

MIT.