Jpdict

jpdict

BundleMode

Bases: str, Enum

How aggressively the stitch function groups UniDic short-unit tokens into words

The modes trade granularity for a learner's needs, from whole dictionary words down to raw morphemes

words

• The coarsest grouping

• Merges compound nouns and the whole inflected tail of a predicate, including the connecting て, bound auxiliary verbs, and politeness, into single dictionary words (e.g. 図書館, 食べてみたかった)

• Best for looking words up

grammar (default)

• The learning view

• Keeps compound nouns and a predicate's inflectional auxiliaries together, but breaks off the pieces a learner parses separately, like the connecting て, bound auxiliary verbs (みる/いる/出す), and the politeness stems (ます/です) (e.g. 食べ | て | みたかった, 読み | ました)

morphemes

• The finest grouping

• No stitching at all, one word per UniDic short unit (e.g. 図書 | 館, 読み | まし | た)

EnrichedJapaneseWord

Bases: BaseModel

A JapaneseWord paired with its dictionary data

Returned by the enrichment endpoint (one kotobase lookup per stitched word), as opposed to the fast tokenize endpoint which returns bare JapaneseWord models

Parameters:

Name	Type	Description	Default
word	JapaneseWord	The stitched word	required
kotobase_data	KotobaseData	The dictionary data for the word's lemma	required

Example

Bases: BaseModel

A single Tatoeba example sentence with its translations

Parameters:

Name	Type	Description	Default
text	str	The Japanese sentence	required
translations	list[str]	English translations of the sentence	required

FuriganaSegment

Bases: BaseModel

One segment of a word's furigana segmentation (JmdictFurigana)

Rendering

• ruby is the text (kanji or kana) and rt is the kana reading annotation of that text (appears on top of ruby in frontend)

• Kana-only words carry no rt, so they render as plain text

Parameters:

Name	Type	Description	Default
ruby	str	The text (kanji or kana)	required
rt	str | None	The kana reading annotation, when the text is kanji	required

JMEntry

Bases: BaseModel

Represents a single word entry in the Japanese-Multilingual Dictionary

freq_rank

• Kotobase derives this field from JMDict's nfxx priority tags, which split the 24000 most common words into 500-word bands

• 1 is the most common band and 48 the least, None means the word is outside the ranked corpus

Parameters:

Name	Type	Description	Default
is_common	bool	Whether any form carries a JMDict common-word priority tag	required
freq_rank	int | None	The 500-word frequency band, when ranked	required
kana	list[str]	Kana reading forms	required
kanji	list[str]	Kanji written forms	required
senses	list[JMWordSense]	The entry's senses, in editorial order	required

JMNEntry

Bases: BaseModel

Represents a single name entry in the Japanese Multi-Lingual Dictionary

Parameters:

Name	Type	Description	Default
kana	list[str]	Kana reading forms	required
kanji	list[str]	Kanji written forms	required
name_types	list[str]	Readable name-type labels (e.g. surname, place name)	required
gloss	list[str]	Translation strings	required

JMWordSense

Bases: BaseModel

Represents a single sense (distinct meanings, translations, or nuances of a Japanese word) for a word within the Japanese-Multilingual Dictionary

Sense Order

• Senses are returned in their editorial order

• They progress from primary, literal definitions to secondary, figurative, or technical nuances

• The order is already preserved in the list returned by kotobase, so no explicit field carries it

Readable Tags

pos, field, and misc carry human-readable labels (e.g. Godan verb with 'u' ending instead of the raw JMDict code v5u), expanded server-side

Parameters:

Name	Type	Description	Default
glosses	list[str]	English equivalents for this sense	required
pos	list[str]	Readable grammatical classifications	required
field	list[str]	Readable subject-domain labels (e.g. medicine)	required
misc	list[str]	Readable usage labels (e.g. colloquial, archaic)	required
antonyms	list[str]	Antonym cross-references	required
xrefs	list[str]	Related-entry cross-references	required

JapaneseWord

Bases: BaseModel

Represents a single useful word stitched from one or more UniDic short-unit tokens

Stitching

• UniDic segments at the short-unit level, which is often too granular to be useful (e.g. 図書館 -> 図書 + 館, or a verb split from its auxiliaries)

• A JapaneseWord re-bundles those short units into the word a learner actually wants to click

• The original short-unit Token models are kept in tokens so no morphological detail is lost

the word built from 読み + まし + た

• surface = "読みました" (the pieces joined as written)
• reading = "ヨミマシタ" (their katakana readings joined)
• lemma = "読む" (the dictionary form, for look-ups)
• pos = "動詞" (verb -- the head piece's part of speech)
• tokens = [読み, まし, た] (the three original short units)

Parameters:

Name	Type	Description	Default
surface	str	The bundle's combined surface form	required
reading	str	The combined katakana reading of the component tokens	required
lemma	str	Dictionary-lookup form (the head token's UniDic's orthBase for inflected words, or the combined surface for noun compounds)	required
pos	str	The head token's top-level part of speech	required
tokens	list[Token]	The component short-unit tokens, in order	required

KanjiAudio

Bases: BaseModel

Pronunciation clips available for a single Kanji (Kanji Alive)

Clips

• Kanji Alive records example-word pronunciations per Kanji, so each clip id names one recorded example word

• A clip's bytes are streamed by the audio clip endpoint using its id

Parameters:

Name	Type	Description	Default
kanji	str	The Kanji literal the clips belong to	required
clips	list[str]	Clip ids, one per recorded example word	required
fmt	str	Audio container format of the clips (e.g. mp3)	required
attribution	str | None	Attribution string required by the source license, when provided	required

KanjiInfo

Bases: BaseModel

Represents a single Kanji entry aggregated from KANJIDIC2, KRADFILE, and KanjiVG

jlpt

• kotobae exposes both the kanji jlpt level from the Tanos study lists, and the pre-2010 KANJIDIC2 level

• The server exposes only one aggreagated jlpt level which prefers the more updataded Tanos level, and falls back to the pre-2010 level when the former is not available

Parameters:

Name	Type	Description	Default
literal	str	Kanji literal	required
grade	int | None	Optional Japanese grade in which Kanji is learned	required
stroke_count	int | None	Number of strokes in handwriting	required
freq	int | None	Frequency-of-use rank (1 = most common), when ranked	required
jlpt	int | None	JLPT level (5 easiest to 1 hardest), when listed	required
is_joyo	bool	Whether the Kanji is in the Joyo (regular use) set	required
meanings	list[str]	List of known meanings	required
onyomi	list[str]	List of on readings	required
kunyomi	list[str]	List of kun readings	required
nanori	list[str]	Name-only readings	required
radicals	list[str]	The Kanji's radical components (KRADFILE)	required
has_stroke_order	bool	Whether a KanjiVG stroke-order SVG exists for this Kanji	required

KotobaseData

Bases: BaseModel

Represents all information extracted from kotobase for a single query (either a single Japanese word, or a wildcard pattern matching multiple words)

meanings

• Exposes the English equivalents contained in the first Japanese-Multilingual Dictionary entry for the query, one string per sense

• If the query has only JMNEntry entries, the first entry's gloss attribute is used

Parameters:

Name	Type	Description	Default
query	str	query literal (either a single Japanese word or a wildcard pattern)	required
jmentries	list[JMEntry]	All Japanese-Multilingual Dictionary entries for the query	required
jmnentries	list[JMNEntry]	All Japanese-Multilingual Dictionary name entries for the query	required
kanji	list[KanjiInfo]	Kanji entries for all Kanji present in the query	required
furigana	list[FuriganaSegment]	Furigana segmentation of the query word's primary form, empty for wildcard queries or unknown words	required
meanings	list[str]	All English equivalents contained in the first JMEntry, or JMNEntry	required
jlpt	str	JLPT vocabulary level for the word extracted from the Tanos list. Defaults to Unknown when it's a wildcard query or the word is not in the list	required
examples	list[Example]	Example sentences (with translations) containing the single word or any words matched by the wildcard query	required

RadicalInfo

Bases: BaseModel

A single search radical (RADKFILE)

Parameters:

Name	Type	Description	Default
radical	str	The radical glyph	required
stroke_count	int | None	The radical's stroke count	required

Token

Bases: BaseModel

Represents morphological data extracted for a single Japanese token

Maps all core token features and deep UniDic morphological data produced by Fugashi. Converts internal dictionary symbols (like asterisks) into clean pythonic types.

Attributes:

Name	Type	Description
surface	str	The raw string exactly as it appears in the text.
lemma	str	The dictionary base form (語彙素) of the word.
reading	str	The standard reading of the token in Katakana.
pos	str	The broad, top-level part of speech (品詞).
pos2	str	Sub-category level 2 part of speech.
pos3	str	Sub-category level 3 part of speech.
pos4	str	Sub-category level 4 part of speech.
c_type	str	Conjugation type (活用型) if applicable.
c_form	str	Conjugation form (活用形) if applicable.
l_form	str	Lemma reading in Katakana.
orth	str	Orthographic surface representation.
pron	str	Actual pronunciation including long vowels.
orth_base	str	Base form using current orthography.
pron_base	str	Pronunciation of the base form.
goshu	str	Word origin type (語種) e.g., Native, Sino-Japanese.
i_type	str	Word-initial transformation type.
i_form	str	Word-initial transformation form.
f_type	str	Word-final transformation type.
f_form	str	Word-final transformation form.

clear_asterisks(data) classmethod

Cleans incoming dictionary fields by converting UniDic's "*" sentinel and any missing (None) feature to an empty string, since unknown / out-of-vocabulary tokens leave some features unset

Parameters:

Name	Type	Description	Default
data	dict	Raw dictionary data containing morphological fields	required

Returns:

Name	Type	Description
dict	dict[str, Any]	The modified dictionary with "*"/None values replaced by ""