ja-entity-parser 1.0.0

Japanese entity parser library for company/corporate name normalization and extraction.

ja-entity-parser

日本語 / English

Overview

ja-entity-parser is a Python library for normalization and extraction of Japanese entities: corporate names, personal names, and addresses.
It combines SudachiPy morphological analysis with custom normalization rules (old/new kanji conversion, kanji numeral conversion, bracket/punctuation/control character unification, NFKC, and user dictionary replacements) to accurately parse Japanese text into structured components.

Features

• Japanese text normalization: Old/new kanji conversion, kanji numeral → Arabic, bracket/punctuation/control character unification, NFKC, corporate abbreviation expansion ((株) → 株式会社, etc.)
• Corporate name parsing: Legal form extraction and brand name/kana via SudachiPy
• Personal name parsing: Family/given name split using SudachiPy POS, whitespace, or surname dictionary
• Address parsing: Prefecture → city → town → block using Address Base Registry data
• User dictionary support: Extendable for industry-specific terms
• Testing: 66 pytest-based unit and integration tests

Installation

pip install ja-entity-parser

Usage

1. Parse corporate name

from ja_entityparser import parse_corporate

result = parse_corporate("トヨタ自動車株式会社")
print(result)
# {
#   'input': 'トヨタ自動車株式会社',
#   'normalized': 'トヨタ自動車株式会社',
#   'legal_form': '株式会社',
#   'brand_name': 'トヨタ自動車',
#   'brand_kana': 'トヨタジドウシャ'
# }

# Abbreviations are automatically expanded:
result = parse_corporate("(株)ソフトバンク")
# normalized: '株式会社ソフトバンク'

2. Parse person name

from ja_entityparser import parse_person

result = parse_person("田中 太郎")
print(result)
# {
#   'input': '田中 太郎',
#   'normalized': '田中 太郎',
#   'family_name': '田中',
#   'given_name': '太郎',
#   'family_name_kana': 'タナカ',
#   'given_name_kana': 'タロウ'
# }

3. Parse address

from ja_entityparser import parse_address

result = parse_address("東京都台東区寿3-1-5")
print(result)
# {
#   'input': '東京都台東区寿3-1-5',
#   'normalized': '東京都台東区寿3-1-5',
#   'prefecture': '東京都',
#   'city': '台東区',
#   'town': '寿',
#   'block': '3-1-5'
# }

Address data is sourced from the Japanese government's アドレス・ベース・レジストリ (Address Base Registry).

4. Normalization only

from ja_entityparser.normalizer import normalize

text = "〔トヨタ〕(株)テスト 三百二十一号"
print(normalize(text))
# (トヨタ)株式会社テスト 321号

API Reference

Function	Description	Returns
parse_corporate(text)	Parse Japanese corporate name	input, normalized, legal_form?, brand_name, brand_kana
parse_person(text)	Parse Japanese person name	input, normalized, family_name?, given_name?, *_kana?
parse_address(text)	Parse Japanese address	input, normalized, prefecture?, city?, town?, block?
normalize(text)	Normalize Japanese text	str

License

Apache License 2.0