SleekRank for kanji character pages
Keep kanji entries in JSON, CSV, or Google Sheets with readings, stroke count, JLPT level, radicals, and example words. SleekRank renders one indexable URL per character at /kanji/{slug}/ from a single base page.
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Kanji datasets belong in JSON, not WordPress posts
A kanji character has a fixed structural shape: on-yomi readings, kun-yomi readings, stroke count, JLPT level, primary radical, secondary radicals, meanings, and example compound words. Public datasets like KANJIDIC already encode all of that as JSON. Pasting two thousand kanji into the WordPress block editor is the wrong direction for the data, and the editor flattens the readings into prose that learners cannot scan.
SleekRank reads the kanji dataset as JSON, CSV, or REST endpoint and emits one indexable WordPress URL per character at /kanji/{slug}/. Tag mappings drop the character into the H1 and meta title, list mappings render the on-yomi and kun-yomi reading arrays, selector mappings handle stroke count and JLPT level, and a separate list mapping renders example words pulled from the same row.
The dataset stays canonical. Adding a JLPT level or revising a meaning is one field update in the source, which flows to the live URL on the next cache refresh. Stroke-order diagrams, audio readings, and example sentences can layer on through additional columns without breaking the base template, and removing a kanji returns a clean 404 on its URL.
Workflow
From kanji dataset to per-character pages
Build the base kanji page
Load the dataset
Wire selectors and lists
Cache for scale
Data in, pages out
From kanji entry to character URL
One row per kanji with readings as JSON arrays, plus stroke count, JLPT level, and example word arrays.
| slug | character | strokes | jlpt | primary_meaning |
|---|---|---|---|---|
| ai | 愛 | 13 | N3 | love |
| mizu | 水 | 4 | N5 | water |
| hi | 火 | 4 | N5 | fire |
| gaku | 学 | 8 | N5 | study |
| shoku | 食 | 9 | N5 | eat |
/kanji/{slug}/
- /kanji/愛/
- /kanji/水/
- /kanji/火/
- /kanji/学/
- /kanji/食/
Comparison
Hand-built kanji posts vs SleekRank
Manual post per character
- Two thousand kanji as individual posts is unmanageable in the editor
- On-yomi and kun-yomi readings render inconsistently across posts
- JLPT level and stroke count fields drift between authors
- Example words get formatted differently from one entry to the next
- Public KANJIDIC data has to be re-keyed by hand into each post
- Bulk corrections (re-tagging JLPT level) touch every entry one at a time
SleekRank
- One URL per kanji from a JSON dataset or sheet
- List mapping renders the on-yomi and kun-yomi reading arrays
- Selector mapping handles stroke count and JLPT level fields
- Example word arrays render through a second list mapping
- Sitemap entries per kanji, base template noindexed
- Edit the dataset, all matching pages refresh on cache cycle
Features
What SleekRank gives you for kanji character pages
Reading arrays as structured lists
On-yomi and kun-yomi readings live as JSON arrays per row. List mappings render them as consistent reading blocks on every kanji page, with the same typography and ordering for every character in the corpus.
Example word compounds
Each character row carries a list of example compounds with their readings and meanings. A list mapping renders them as a reference block on the page, so learners see real usage alongside the structural fields.
JLPT and stroke filters
JLPT level and stroke count fields drive automatic filter pages via separate page groups against the same source. A new kanji appears in its JLPT level cluster and its stroke-count cluster automatically on the next cache cycle.
Use cases
Where kanji libraries run on SleekRank
Japanese language schools
Run a per-kanji reference library that complements the curriculum. Each character gets one stable indexable URL that lesson plans link to, with consistent reading and stroke-count formatting across all entries.
JLPT prep platforms
Publish kanji libraries grouped by JLPT level for learner SEO. Search traffic for character-specific queries lands on a structured page that shows readings, meanings, and example compounds without the editor lock-in.
Linguistics references
Academic sites publish a structured kanji reference where every character carries the same field set. The dataset stays in JSON where linguists already maintain it, and the WordPress site becomes a presentation layer.
The bigger picture
Why kanji datasets do not belong inside the block editor
A kanji is a row in a public dataset. Two thousand characters share the same field structure with different values, and the differences are pure data, not editorial choices. Pasting them into individual WordPress posts loses the structure, locks the dataset into the WordPress editor, and makes any bulk operation (re-tagging JLPT, refreshing example words, adding stroke-order diagrams to every character) effectively impossible.
Public datasets like KANJIDIC already encode every field a learner needs, and they ship as JSON. The right move is to leave them there and treat WordPress as the rendering layer over the dataset. SleekRank turns a kanji JSON file into one indexable URL per character with consistent readings, stroke counts, JLPT badges, and example compounds across every entry.
The dataset stays canonical, the layout stays in the template, and the corpus grows or refreshes with a single cache clear. Learners get a clean structured page per character, search engines get a sitemap covering every entry, and the team maintaining the site never has to open the WordPress editor to add or update a kanji.
Questions
Common questions about SleekRank for kanji character pages
Yes. The source dataset is read once per cache window, then per-request rendering pulls only the row needed for the URL being viewed. Set cacheDuration to several hours since the dataset is essentially static and indexing performance stays steady across the full corpus.
 Store each as its own JSON array column on the row. Two separate list mappings render them into distinct labelled blocks on the page (one on-yomi block, one kun-yomi block). The structural distinction stays clear regardless of how many readings each character has.
 Yes. Add a stroke-order image URL column and an audio URL column per character. Tag mappings inject the image as an HTML element, and the audio URL maps to an HTML5 audio element. Storage stays in your media library or a CDN; the dataset only carries the URLs.
 Either works. Using the reading (ai, mizu, hi) gives ASCII URLs that are universally cite-able. Using the character itself gives shorter URLs but requires confirming the URL pattern handles Unicode correctly for your hosting. Whichever you pick, keep it consistent across the dataset.
 Edit the source field, clear the SleekRank cache, and the next request pulls the corrected reading. Bulk corrections to JLPT levels or re-tagging across many characters land everywhere on a single cache flush, which is the entire reason the dataset lives separately from the WordPress posts.
 Yes. Each character is a routable WordPress URL included in the sitemap with its own canonical, title, and meta description sourced from your mappings. The base template is auto-noindexed so the scaffolding does not compete with real kanji pages in search results.
 Yes. Create a second page group with its own data source that filters the same JSON to JLPT N5 (or similar), and its own urlPattern like /jlpt/n5/{slug}/. Both groups read from the same source, so adding a kanji updates both clusters on the next cache cycle.
 Yes. Vocabulary lists, grammar points, and example sentences can live in separate sources. Map each one to slots on the base kanji page and SleekRank merges them at render time, keyed by the kanji slug. The page becomes a multi-source reference without re-keying any data.
 Pricing
More than 1000+
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Explore our flexible licensing options tailored to your needs. Upgrade your license anytime to access more features, or opt for a lifetime license for ongoing value, including lifetime updates and lifetime support. Our hassle-free upgrade process ensures that our platform can grow with you, starting from whichever plan you choose.
Starter
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per year
further 30% launch-discount applied during checkout for existing customers.
- 3 websites
- 1 year of updates
- 1 year of support
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further 30% launch-discount applied during checkout for existing customers.
- Unlimited websites
- 1 year of updates
- 1 year of support
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Launch Offer
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EUR
once
further 30% launch-discount applied during checkout for existing customers.
- Unlimited websites
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- Lifetime support
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