List Detailing 1714 of Japan's Municipalities' Placenames with Tokenised Hiragana (日本地方自治体の地名のトークン化された平仮名からなるデータセット)

Consider the town Kakuda-Shi 角田市.
This is written in datasets and dictionaries as かくだし.
Is that broken down as か,く,だし, か,くだ,し, or かく,だ,し?
A Japanese person will know that it is the latter intuitively.

NLP and AI parsers were highly innaccurate identifying the context-specific reading of a given placename-nested kanji across the 1737 entries in this list (1714 municipalities + 23 regional subdivision 'wards' of Tokyo). This is because many placename kanji readings deviate significantly from common readings.

I manually tokenised these placenames as such. There is a JSON with keys, a JSON as objects, and a CSV for GUI editing. Because I've done it by hand, and because I'm not Japanese, there may be some discrepancies.

Format

{
   "code": 292010,
   "name_kanji": "奈良市",
   "name_kana": "ならし",
   "name_kana_breakdown": "な,ら,し",
   "name_romaji": "Nara Shi",
   "prefecture_kanji": "奈良県",
   "prefecture_kana": "ならけん",
   "prefecture_kana_breakdown": "な,ら,けん",
   "prefecture_romaji": "Nara Ken",
   "latitude": 34.68333333,
   "longitude": 135.8
 },
 {
   "code": 292028,
   "name_kanji": "大和高田市",
   "name_kana": "やまとたかだし",
   "name_kana_breakdown": "やまと,たか,だ,し",
   "name_kana_notes": "Irregular reading: 大和 (やまと) does not decompose to two separate kanji readings",
   "name_romaji": "Yamatotakada Shi",
   "prefecture_kanji": "奈良県",
   "prefecture_kana": "ならけん",
   "prefecture_kana_breakdown": "な,ら,けん",
   "prefecture_romaji": "Nara Ken",
   "latitude": 34.5,
   "longitude": 135.7333333
 },

Acknowledgements

This dataset is built upon Fabio Crisci's open-data-jp-municipalities. That list was extracted from the Gazetteer of Japan 2007/2018, the original 2007 Github repo of which can be found here. Prefecture information comes from here.