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Downstep compound pitch-accent benchmark: 89,539 compounds, listed/unlisted/hard

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  2. README.md +268 -0
  3. baseline_results.json +1834 -0
  4. dev.jsonl +0 -0
  5. mora_validation.json +1083 -0
  6. stats.json +60 -0
  7. test.jsonl +0 -0
  8. train.jsonl +3 -0
.gitattributes CHANGED
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
 
 
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  # Video files - compressed
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  *.mp4 filter=lfs diff=lfs merge=lfs -text
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  *.webm filter=lfs diff=lfs merge=lfs -text
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+ train.jsonl filter=lfs diff=lfs merge=lfs -text
README.md ADDED
@@ -0,0 +1,268 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ ---
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+ language:
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+ - ja
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+ license: bsd-3-clause
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+ license_link: https://opensource.org/license/bsd-3-clause
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+ pretty_name: Downstep compound pitch-accent benchmark (listed / unlisted / hard)
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+ task_categories:
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+ - token-classification
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+ tags:
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+ - japanese
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+ - pitch-accent
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+ - prosody
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+ - tts
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+ - openjtalk
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+ - compounds
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+ - generalization
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+ - data-splits
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+ - multi-label
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+ annotations_creators:
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+ - machine-generated
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+ language_creators:
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+ - expert-generated
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+ size_categories:
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+ - 10K<n<100K
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+ configs:
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+ - config_name: default
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+ data_files:
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+ - split: train
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+ path: train.jsonl
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+ - split: dev
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+ path: dev.jsonl
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+ - split: test
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+ path: test.jsonl
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+ ---
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+
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+ # Downstep compound pitch-accent benchmark
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+
38
+ **Japanese noun compounds, their mora segmentation, and every accent their source
39
+ dictionaries attest. Built so that "the model has never seen this compound" is a
40
+ condition you can actually turn on, rather than a claim you have to trust.**
41
+
42
+ > **No human annotation is present in this release.** Every accent label here is
43
+ > dictionary-derived. `docs/ANNOTATION_GUIDELINES.md` ships the protocol, the CSV
44
+ > format and the agreement statistics for collecting native-speaker judgements on
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+ > novel compounds — but that collection has not happened, and nothing in this
46
+ > repository should be read as if it had. There are no annotator IDs, no agreement
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+ > scores and no human-adjudicated items.
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+
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+ ---
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+
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+ ## Sources and licences
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+
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+ Two independently produced lexicons. Downstep reads the copies installed by
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+ `unidic-lite` and `pyopenjtalk` and never fetches anything over the network.
55
+
56
+ | Source | Holder | Licence | Reached via |
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+ |---|---|---|---|
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+ | **UniDic 2.1.2** (unidic-mecab) | The UniDic Consortium / NINJAL | GPL **/** LGPL **/** BSD 3-Clause, tri-licensed — **Downstep relies on the BSD option** | `unidic-lite` |
59
+ | **NAIST-jdic** (Open JTalk's system dictionary) | Nara Institute of Science and Technology | BSD 3-Clause | `pyopenjtalk` |
60
+
61
+ **Attribution both licences require**, reproduced in full in [`NOTICE`](../NOTICE) and
62
+ required of anyone redistributing these rows:
63
+
64
+ - Retain the copyright notice, the list of BSD 3-Clause conditions and the warranty
65
+ disclaimer.
66
+ - Do **not** use "The UniDic Consortium", "NINJAL", "Nara Institute of Science and
67
+ Technology" or their contributors to endorse or promote anything derived from this
68
+ data without prior written permission. Downstep makes no such endorsement claim.
69
+
70
+ The BSD option is what makes the derived rows redistributable at all: under the GPL
71
+ option a redistributed derivative would have to be GPL, which is why the choice is
72
+ stated explicitly rather than left to the reader.
73
+
74
+ The tooling in this repository is Apache-2.0. The data rows below are governed by
75
+ BSD 3-Clause through their sources.
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+
77
+ ### What is redistributed, and what is not
78
+
79
+ **Redistributed:** derived rows — surface, reading, mora segmentation, the set of
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+ attested accents, the component decomposition, and the split/stratum labels.
81
+
82
+ **Not redistributed:** the dictionaries themselves, in compiled or CSV form; any
83
+ audio; any human judgement. `downstep.lexicon.load_lexicons()` rebuilds the local
84
+ cache (`data/lexicon/*.jsonl`, git-ignored) from the installed packages in ~20 s.
85
+
86
+ Measured in the cached dump on 2026-09-03 (`make lexicon`, then a count over the
87
+ JSONL):
88
+
89
+ | | UniDic 2.1.2 | NAIST-jdic |
90
+ |---|---:|---:|
91
+ | entries | 751,705 | 788,331 |
92
+ | distinct surfaces | 568,123 | 461,975 |
93
+ | noun entries | 277,189 | 455,743 |
94
+ | distinct noun surfaces with an accent | 258,371 | 418,671 |
95
+ | noun entries recording **more than one** accent | 21,568 | 0 |
96
+ | noun surfaces whose accents disagree **across** entries | 24,844 | 5,854 |
97
+
98
+ Those two right-hand columns are the raw material for the multiple-answer field.
99
+ NAIST-jdic records one accent per entry, so its variation only appears when two
100
+ entries share a surface; UniDic records variation inside a single entry
101
+ (`"0,4,3,1"`, CSV-quoted — a naive `split(",")` both mis-counts the fields and
102
+ destroys exactly these rows).
103
+
104
+ ---
105
+
106
+ ## What one row is
107
+
108
+ A noun compound that satisfies **both** of:
109
+
110
+ 1. It is a lexicalised entry in NAIST-jdic, so a lexicographer assigned it an accent.
111
+ That is the gold.
112
+ 2. It decomposes into **two or more** morphemes whose readings compose back to the
113
+ compound's own reading, with 連濁 / 促音化 accounted for. That is what makes it a
114
+ composition problem rather than a lookup.
115
+
116
+ Cut points for (2) are constrained to a morphological analyser's boundaries. The
117
+ analyser is **UniDic** while the gold is **NAIST-jdic** — deliberately a different
118
+ dictionary, so the decomposition is not read off the answer. Without that constraint
119
+ the decomposition collapses: a naive dynamic program over dictionary surfaces splits
120
+ ファインマン into ファ+イン+マ+ン, because nearly every single kana is itself an entry,
121
+ and reading-consistency alone cannot reject it.
122
+
123
+ ## Fields
124
+
125
+ | Field | Type | Description |
126
+ |---|---|---|
127
+ | `surface` | str | The compound |
128
+ | `reading` | str | Katakana reading, devoicing marks and interpuncts removed |
129
+ | `moras` | list[str] | Mora segmentation; `len(moras) == n_moras` is enforced at build time |
130
+ | `n_moras` | int | Mora count |
131
+ | `gold_accents` | list[int] | **A set, not a value.** `0` = 平板; `k` = nucleus on mora `k`, 1-indexed |
132
+ | `has_variation` | bool | `len(gold_accents) > 1` — the dictionaries attest more than one accent |
133
+ | `components` | list[obj] | Per component: `surface`, `reading`, `accent`, `n_moras`, `goshu`, `acon_type`, `in_lexicon` |
134
+ | `n_components` | int | Number of components (always ≥ 2) |
135
+ | `goshu` | str | 語種 of the compound, taken as the modal component value (和 / 漢 / 外 / 固 / 混) |
136
+ | `script` | str | `kanji` / `katakana` / `mixed` |
137
+ | `is_proper` | bool | The NAIST entry's POS is 固有名詞 |
138
+ | `all_components_in_lexicon` | bool | Every component was found in a source lexicon |
139
+ | `split` | str | `train` / `dev` / `test` |
140
+ | `hard` | bool | Test-only: **no** component of this compound occurs in any training compound |
141
+ | `source` | str | `naist-jdic`, or `naist-jdic+unidic` when the accent set draws on both |
142
+
143
+ ### `gold_accents` is the multiple-accepted-answers field
144
+
145
+ Japanese pitch accent genuinely admits more than one correct answer for many words,
146
+ and the dictionaries record that. Scoring against a single "true" accent would
147
+ manufacture errors out of real variation. So:
148
+
149
+ - **Score membership**, not equality: a prediction is correct if it is *in*
150
+ `gold_accents`. `downstep.metrics.nucleus_exact_match` takes a set.
151
+ - `has_variation` marks these rows so they can be reported as their own stratum,
152
+ because a system that always guesses the majority variant looks better on them than
153
+ it deserves.
154
+ - This field records **lexicographic** variation between and within dictionaries. It
155
+ is not, and must not be presented as, a survey of how speakers pronounce these
156
+ words.
157
+
158
+ ---
159
+
160
+ ## Splits, conditions and strata — three different things
161
+
162
+ **Splits** partition the rows. Assignment is `sha1(surface)` thresholded, not a
163
+ shuffled seed, so adding new candidate words never moves an existing word between
164
+ splits and any machine reproduces the same partition.
165
+
166
+ | split | share | rows |
167
+ |---|---|---|
168
+ | `train` | 79.9% | **71,544** |
169
+ | `dev` | 10.0% (calibration and abstention threshold) | **8,959** |
170
+ | `test` | 10.1% | **9,036** |
171
+
172
+ Total: **89,539** compounds.
173
+
174
+ **Conditions** are not splits. `listed` and `unlisted` are the *same* test rows
175
+ evaluated twice, with the dictionary's whole-word entry present and then ablated at
176
+ query time. See [`docs/METHODOLOGY.md`](../docs/METHODOLOGY.md) for why the ablation
177
+ must be rebuilt per target — batching corrupted 47.7% of targets in the pilot.
178
+
179
+ **`hard` is a partition of the test set.** Two nested flags:
180
+
181
+ * `hard` (818 rows, 9.0% of test) — the
182
+ compound's **final** morpheme never occurs in any training compound. The final element
183
+ (後部要素) governs compound accent in the classical rules, so this is the linguistically
184
+ meaningful generalisation test.
185
+ * `hard_all` (105 rows) — *no* component occurs in training. Stricter,
186
+ but too small to carry a claim; kept as a stratum.
187
+
188
+ Reported separately, never averaged into the headline: a pilot found a memorisation-shaped
189
+ model gained **nothing** on unseen final components (58.3% vs 58.3%). The trained model does
190
+ better than that — but the split exists so that can be checked rather than assumed.
191
+
192
+ | stratum field | why it is a stratum |
193
+ |---|---|
194
+ | `is_proper` | Proper nouns are a different problem with different conventions; they are 66% of these rows (59,430 of 89,539) and are **reported on their own**, never folded into a single number |
195
+ | `goshu` | 和語 / 漢語 / 外来語 compounds follow different accent regularities |
196
+ | `n_components` | Two-part compounds are much easier than three-part ones |
197
+ | `n_moras` | Longer compounds have more positions to get wrong |
198
+ | `has_variation` | Rows with more than one accepted answer |
199
+ | `script` | Katakana (largely loanword) compounds behave unlike kanji ones |
200
+
201
+ Row counts, from `benchmarks/stats.json`:
202
+
203
+ | stratum | counts |
204
+ |---|---|
205
+ | script | kanji 55,237 · mixed 27,290 · katakana 7,012 |
206
+ | 語種 (`goshu`) | 和 34,760 · 固 25,085 · 漢 23,313 · 外 4,443 · 混 604 · 記号 570 · unknown 764 |
207
+ | components | 2 → 70,419 · 3 → 16,286 · 4 → 2,539 · 5+ → 295 |
208
+ | moras | 4 → 21,228 · 5 → 19,522 · 6 → 18,884 · 7 → 11,112 · 8+ → 18,793 |
209
+ | noun type | proper 59,430 · common 30,109 |
210
+ | more than one attested accent | **1,030** |
211
+ | every component in a lexicon | 89,539 (all of them — decomposition requires it) |
212
+
213
+ ---
214
+
215
+ ## Limitations, stated plainly
216
+
217
+ - **The gold is a dictionary's opinion.** Dictionaries disagree with each other and
218
+ with speakers. Where they disagree with each other the row keeps both answers; where
219
+ they disagree with speakers, this data cannot tell.
220
+ - **The variety recorded is a broadly Tokyo-based standard.** That is what these two
221
+ lexicons encode, so it is a scoping decision forced by the available data. It is
222
+ **not** a claim that other regional or generational accent systems are incorrect, and
223
+ a Downstep prediction is not a correction of anyone's speech.
224
+ - **These are all words that exist in a dictionary.** The target application is
225
+ compounds that do not. The ablation device is what bridges that gap, and its limits
226
+ are argued — not waved away — in `docs/METHODOLOGY.md`.
227
+ - **Reading-consistent decomposition rejects real compounds.** The rendaku model covers
228
+ 連濁 and 促音化 but not 連声 or stem alternations (雨 → あま, 酒 → さか), so compounds
229
+ built on those are dropped rather than mis-segmented. That is a coverage limitation
230
+ the numbers do not show.
231
+ - **No speech.** No F0 contours, no durations, no speaker information. Accent here is
232
+ an integer, not a measurement.
233
+ - **Not a pronunciation dictionary.** Do not use these rows as a reference for how a
234
+ word "should" be said. For that, consult NHK日本語発音アクセント新辞典 or
235
+ 明解日本語アクセント辞典.
236
+
237
+ ## Out-of-scope uses
238
+
239
+ - As an authority on correct pronunciation, in education or assessment.
240
+ - To evaluate or rank speakers, or to flag any pronunciation as an error.
241
+ - As evidence about regional variation, which it contains no information about.
242
+
243
+ ## Reproducing
244
+
245
+ ```bash
246
+ pip install -e ".[all]"
247
+ make bench # writes benchmarks/{train,dev,test}.jsonl and benchmarks/stats.json
248
+ ```
249
+
250
+ `scripts/build_bench.py` is the only path from the two dictionaries to these rows,
251
+ and it asserts its own `hard` property rather than trusting it. Nothing is pushed
252
+ anywhere: `--push` exists, defaults off, and refuses to publish on its own.
253
+
254
+ ## Citation
255
+
256
+ ```
257
+ Downstep: a compound pitch-accent benchmark with a dictionary-ablation
258
+ condition for words the TTS dictionary does not have.
259
+ Derived from UniDic 2.1.2 (The UniDic Consortium / NINJAL, BSD-3 option)
260
+ and NAIST-jdic (Nara Institute of Science and Technology, BSD-3).
261
+ No human annotation.
262
+ ```
263
+
264
+ ---
265
+
266
+ *Substantiates: **unlisted-word accuracy** — these rows plus the ablation condition are
267
+ what "the dictionary does not have this compound" is measured on; and **reproducibility**,
268
+ since `make bench` is the only path from the two dictionaries to them.*
baseline_results.json ADDED
@@ -0,0 +1,1834 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ {
2
+ "generated_by": "scripts/evaluate.py",
3
+ "checkpoint": "checkpoints/base",
4
+ "conditions": {
5
+ "listed": {
6
+ "n_items": 9036,
7
+ "n_reading_matched": 5414,
8
+ "n_reading_ok_this_condition": 8815,
9
+ "n_excluded_for_reading": 3622,
10
+ "openjtalk_seconds": 0.61,
11
+ "downstep_seconds": 18.13,
12
+ "strata": {
13
+ "all": {
14
+ "n": 5414,
15
+ "A_openjtalk": 0.9637975618766161,
16
+ "B_dictionary": 1.0,
17
+ "A_wrongly_split": 0.022349464351680826,
18
+ "C_downstep": 0.8134466198743997,
19
+ "C_wrongly_split": 0.0
20
+ },
21
+ "common_nouns": {
22
+ "n": 2033,
23
+ "A_openjtalk": 0.9567142154451549,
24
+ "B_dictionary": 1.0,
25
+ "A_wrongly_split": 0.017707820954254796,
26
+ "C_downstep": 0.7968519429414658,
27
+ "C_wrongly_split": 0.0
28
+ },
29
+ "proper_nouns": {
30
+ "n": 3381,
31
+ "A_openjtalk": 0.9680567879325643,
32
+ "B_dictionary": 1.0,
33
+ "A_wrongly_split": 0.025140490979000295,
34
+ "C_downstep": 0.8234250221827861,
35
+ "C_wrongly_split": 0.0
36
+ },
37
+ "hard": {
38
+ "n": 574,
39
+ "A_openjtalk": 0.9686411149825784,
40
+ "B_dictionary": 1.0,
41
+ "A_wrongly_split": 0.0156794425087108,
42
+ "C_downstep": 0.7334494773519163,
43
+ "C_wrongly_split": 0.0
44
+ },
45
+ "hard_all": {
46
+ "n": 98,
47
+ "A_openjtalk": 0.9897959183673469,
48
+ "B_dictionary": 1.0,
49
+ "A_wrongly_split": 0.0,
50
+ "C_downstep": 0.6224489795918368,
51
+ "C_wrongly_split": 0.0
52
+ },
53
+ "variation": {
54
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+ "baseline_accuracy": 0.4059844846693757,
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+ "ece": 0.0576062929816676
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+ "nbest_coverage": {
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+ "variation_only": {
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+ "1": 0.6122448979591837,
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+ "5": 1.0
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+ },
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+ "n_variation": 49
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+ },
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+ "operating_point_dev_chosen": {
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+ "chosen_on": "dev split, same condition",
1808
+ "max_accuracy": {
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+ "coverage": 1.0,
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+ "combined_accuracy": 0.8134466198743997,
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+ "regressions": 256,
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+ "improvements": 2462,
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+ "n": 5414
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+ },
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+ "zero_regression_on_dev": {
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+ "threshold": 0.997893,
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+ "combined_accuracy": 0.42223864056150723,
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+ "regressions": 0,
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+ "improvements": 88,
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+ "dev_zero_regression_coverage": 0.08007448789571694
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+ }
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+ },
1828
+ "notes": {
1829
+ "fairness": "Accuracy is computed on items where OpenJTalk's own reading matched the gold reading, so the comparison is about accent rather than G2P.",
1830
+ "downstep_condition_invariance": "Downstep's prediction does not depend on the condition: it reads components, never the compound's own dictionary entry.",
1831
+ "no_human_annotation": "All gold is dictionary-derived. No native-speaker annotation was collected for this release.",
1832
+ "comparable_set": "Strata are scored on the 5,414 test compounds whose reading OpenJTalk produced correctly in BOTH the listed and the unlisted condition, so the two columns describe the same words."
1833
+ }
1834
+ }
dev.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
mora_validation.json ADDED
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1
+ {
2
+ "tool": "scripts/validate_mora.py",
3
+ "generated_at": "2026-09-03T16:16:51+0900",
4
+ "elapsed_seconds": 19.26,
5
+ "environment": {
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+ "python": "3.13.5",
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+ "platform": "macOS-26.6.2-arm64-arm-64bit-Mach-O"
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+ },
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+ "tokenizer": {
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+ "module": "downstep.mora",
11
+ "fold_small_counters": true,
12
+ "strict": false,
13
+ "rules": {
14
+ "small_kana_fuse_with_the_preceding_kana": [
15
+ "ァ",
16
+ "ィ",
17
+ "ゥ",
18
+ "ェ",
19
+ "ォ",
20
+ "ャ",
21
+ "ュ",
22
+ "ョ",
23
+ "ヮ"
24
+ ],
25
+ "own_mora": [
26
+ "ッ",
27
+ "ン",
28
+ "ー"
29
+ ],
30
+ "small_counters_folded_to_full": {
31
+ "ヵ": "カ",
32
+ "ヶ": "ケ"
33
+ }
34
+ }
35
+ },
36
+ "documented_examples": {
37
+ "note": "definitions taken from downstep/mora.py's own docstring plus mechanical applications of the four rules it states; not a measurement",
38
+ "n": 29,
39
+ "passed": 29,
40
+ "failed": 0,
41
+ "failures": []
42
+ },
43
+ "losslessness": {
44
+ "checked": 788331,
45
+ "lossless": 788331,
46
+ "n_failures": 0,
47
+ "failures_shown": []
48
+ },
49
+ "naist": {
50
+ "source": "NAIST Japanese Dictionary (naist-jdic), as shipped with Open JTalk",
51
+ "check": "direct: tokenizer mora count vs the dictionary's own accmora denominator",
52
+ "devoicing_marks_stripped": [
53
+ "’",
54
+ "'"
55
+ ],
56
+ "entries_read": 788331,
57
+ "entries_without_recorded_count": 0,
58
+ "entries_with_recorded_count": 788331,
59
+ "agree": 788190,
60
+ "disagree": 141,
61
+ "agreement_rate": 0.9998211411196566,
62
+ "delta_histogram": {
63
+ "1": 138,
64
+ "2": 1,
65
+ "3": 2
66
+ },
67
+ "attribution": {
68
+ "rule": "a kana pair the tokenizer fuses into one mora is blamed only if it occurs in zero agreeing entries; the dictionary then evidently counts it as two. Completeness is verified by recounting every disagreeing entry under that assumption.",
69
+ "explained": 141,
70
+ "unexplained": 0,
71
+ "unexplained_rows": [],
72
+ "n_pairs": 33,
73
+ "pairs": [
74
+ {
75
+ "mora": "フュ",
76
+ "mechanism": "palatalisation_on_a_non_standard_base",
77
+ "disagreeing_rows_containing_it": 67,
78
+ "agreeing_rows_containing_it": 0,
79
+ "examples": [
80
+ {
81
+ "surface": "ふゅーじょん",
82
+ "reading": "フュージョン",
83
+ "dict_moras": 5,
84
+ "tokenizer_moras": 4
85
+ },
86
+ {
87
+ "surface": "アフュス",
88
+ "reading": "アフュス",
89
+ "dict_moras": 4,
90
+ "tokenizer_moras": 3
91
+ },
92
+ {
93
+ "surface": "アフュティス",
94
+ "reading": "アフュティス",
95
+ "dict_moras": 5,
96
+ "tokenizer_moras": 4
97
+ },
98
+ {
99
+ "surface": "インフューザー",
100
+ "reading": "インフューザー",
101
+ "dict_moras": 7,
102
+ "tokenizer_moras": 6
103
+ }
104
+ ]
105
+ },
106
+ {
107
+ "mora": "イュ",
108
+ "mechanism": "palatalisation_on_a_non_standard_base",
109
+ "disagreeing_rows_containing_it": 12,
110
+ "agreeing_rows_containing_it": 0,
111
+ "examples": [
112
+ {
113
+ "surface": "かいい",
114
+ "reading": "カイュー",
115
+ "dict_moras": 4,
116
+ "tokenizer_moras": 3
117
+ },
118
+ {
119
+ "surface": "かっわいい",
120
+ "reading": "カッワイュー",
121
+ "dict_moras": 6,
122
+ "tokenizer_moras": 5
123
+ },
124
+ {
125
+ "surface": "かわいい",
126
+ "reading": "カワイュウ",
127
+ "dict_moras": 5,
128
+ "tokenizer_moras": 4
129
+ },
130
+ {
131
+ "surface": "かわいい",
132
+ "reading": "カワイュウ",
133
+ "dict_moras": 5,
134
+ "tokenizer_moras": 4
135
+ }
136
+ ]
137
+ },
138
+ {
139
+ "mora": "クォ",
140
+ "mechanism": "small_vowel_after_a_full_kana",
141
+ "disagreeing_rows_containing_it": 5,
142
+ "agreeing_rows_containing_it": 0,
143
+ "examples": [
144
+ {
145
+ "surface": "クォータリー",
146
+ "reading": "クォータリー",
147
+ "dict_moras": 6,
148
+ "tokenizer_moras": 5
149
+ },
150
+ {
151
+ "surface": "クォーター",
152
+ "reading": "クォーター",
153
+ "dict_moras": 5,
154
+ "tokenizer_moras": 4
155
+ },
156
+ {
157
+ "surface": "クォーテーション",
158
+ "reading": "クォーテーション",
159
+ "dict_moras": 7,
160
+ "tokenizer_moras": 6
161
+ },
162
+ {
163
+ "surface": "クォート",
164
+ "reading": "クォート",
165
+ "dict_moras": 4,
166
+ "tokenizer_moras": 3
167
+ }
168
+ ]
169
+ },
170
+ {
171
+ "mora": "シィ",
172
+ "mechanism": "small_vowel_after_a_full_kana",
173
+ "disagreeing_rows_containing_it": 5,
174
+ "agreeing_rows_containing_it": 0,
175
+ "examples": [
176
+ {
177
+ "surface": "アイディシィソリューションズ",
178
+ "reading": "アイディシィソリューションズ",
179
+ "dict_moras": 11,
180
+ "tokenizer_moras": 10
181
+ },
182
+ {
183
+ "surface": "エフ・ディ・シィ・プロダクツ",
184
+ "reading": "エフディシィプロダクツ",
185
+ "dict_moras": 10,
186
+ "tokenizer_moras": 9
187
+ },
188
+ {
189
+ "surface": "ルートフィッシィング",
190
+ "reading": "ルートフィッシィング",
191
+ "dict_moras": 9,
192
+ "tokenizer_moras": 8
193
+ },
194
+ {
195
+ "surface": "レガシィ",
196
+ "reading": "レガシィ",
197
+ "dict_moras": 4,
198
+ "tokenizer_moras": 3
199
+ }
200
+ ]
201
+ },
202
+ {
203
+ "mora": "ヂャ",
204
+ "mechanism": "youon_written_on_the_di_row_historical_orthography",
205
+ "disagreeing_rows_containing_it": 5,
206
+ "agreeing_rows_containing_it": 0,
207
+ "examples": [
208
+ {
209
+ "surface": "ぢゃぢゅぢょ",
210
+ "reading": "ヂャヂュヂョ",
211
+ "dict_moras": 6,
212
+ "tokenizer_moras": 3
213
+ },
214
+ {
215
+ "surface": "ヂャヂュヂョ",
216
+ "reading": "ヂャヂュヂョ",
217
+ "dict_moras": 6,
218
+ "tokenizer_moras": 3
219
+ },
220
+ {
221
+ "surface": "茶",
222
+ "reading": "ヂャ",
223
+ "dict_moras": 2,
224
+ "tokenizer_moras": 1
225
+ },
226
+ {
227
+ "surface": "茶屋",
228
+ "reading": "ヂャヤ",
229
+ "dict_moras": 3,
230
+ "tokenizer_moras": 2
231
+ }
232
+ ]
233
+ },
234
+ {
235
+ "mora": "ヂョ",
236
+ "mechanism": "youon_written_on_the_di_row_historical_orthography",
237
+ "disagreeing_rows_containing_it": 5,
238
+ "agreeing_rows_containing_it": 0,
239
+ "examples": [
240
+ {
241
+ "surface": "ぢゃぢゅぢょ",
242
+ "reading": "ヂャヂュヂョ",
243
+ "dict_moras": 6,
244
+ "tokenizer_moras": 3
245
+ },
246
+ {
247
+ "surface": "ヂャヂュヂョ",
248
+ "reading": "ヂャヂュヂョ",
249
+ "dict_moras": 6,
250
+ "tokenizer_moras": 3
251
+ },
252
+ {
253
+ "surface": "提灯",
254
+ "reading": "ヂョウチン",
255
+ "dict_moras": 5,
256
+ "tokenizer_moras": 4
257
+ },
258
+ {
259
+ "surface": "提灯",
260
+ "reading": "ヂョウチン",
261
+ "dict_moras": 5,
262
+ "tokenizer_moras": 4
263
+ }
264
+ ]
265
+ },
266
+ {
267
+ "mora": "クィ",
268
+ "mechanism": "small_vowel_after_a_full_kana",
269
+ "disagreeing_rows_containing_it": 4,
270
+ "agreeing_rows_containing_it": 0,
271
+ "examples": [
272
+ {
273
+ "surface": "クィック",
274
+ "reading": "クィック",
275
+ "dict_moras": 4,
276
+ "tokenizer_moras": 3
277
+ },
278
+ {
279
+ "surface": "クィックソート",
280
+ "reading": "クィックソート",
281
+ "dict_moras": 7,
282
+ "tokenizer_moras": 6
283
+ },
284
+ {
285
+ "surface": "クィンテット",
286
+ "reading": "クィンテット",
287
+ "dict_moras": 6,
288
+ "tokenizer_moras": 5
289
+ },
290
+ {
291
+ "surface": "ラブリークィーン",
292
+ "reading": "ラブリークィーン",
293
+ "dict_moras": 8,
294
+ "tokenizer_moras": 7
295
+ }
296
+ ]
297
+ },
298
+ {
299
+ "mora": "ナュ",
300
+ "mechanism": "palatalisation_on_a_non_standard_base",
301
+ "disagreeing_rows_containing_it": 4,
302
+ "agreeing_rows_containing_it": 0,
303
+ "examples": [
304
+ {
305
+ "surface": "とんでもない",
306
+ "reading": "トンデモナュウ",
307
+ "dict_moras": 7,
308
+ "tokenizer_moras": 6
309
+ },
310
+ {
311
+ "surface": "とんでもない",
312
+ "reading": "トンデモナュウ",
313
+ "dict_moras": 7,
314
+ "tokenizer_moras": 6
315
+ },
316
+ {
317
+ "surface": "無い",
318
+ "reading": "ナュー",
319
+ "dict_moras": 3,
320
+ "tokenizer_moras": 2
321
+ },
322
+ {
323
+ "surface": "無い",
324
+ "reading": "ナュー",
325
+ "dict_moras": 3,
326
+ "tokenizer_moras": 2
327
+ }
328
+ ]
329
+ },
330
+ {
331
+ "mora": "クァ",
332
+ "mechanism": "small_vowel_after_a_full_kana",
333
+ "disagreeing_rows_containing_it": 3,
334
+ "agreeing_rows_containing_it": 0,
335
+ "examples": [
336
+ {
337
+ "surface": "クァルテット",
338
+ "reading": "クァルテット",
339
+ "dict_moras": 6,
340
+ "tokenizer_moras": 5
341
+ },
342
+ {
343
+ "surface": "クァンジュ",
344
+ "reading": "クァンジュ",
345
+ "dict_moras": 4,
346
+ "tokenizer_moras": 3
347
+ },
348
+ {
349
+ "surface": "高広鎮",
350
+ "reading": "コークァンジン",
351
+ "dict_moras": 7,
352
+ "tokenizer_moras": 6
353
+ }
354
+ ]
355
+ },
356
+ {
357
+ "mora": "クェ",
358
+ "mechanism": "small_vowel_after_a_full_kana",
359
+ "disagreeing_rows_containing_it": 3,
360
+ "agreeing_rows_containing_it": 0,
361
+ "examples": [
362
+ {
363
+ "surface": "クェスチョン",
364
+ "reading": "クェスチョン",
365
+ "dict_moras": 5,
366
+ "tokenizer_moras": 4
367
+ },
368
+ {
369
+ "surface": "クェッション",
370
+ "reading": "クェッション",
371
+ "dict_moras": 5,
372
+ "tokenizer_moras": 4
373
+ },
374
+ {
375
+ "surface": "AFLACスクェア",
376
+ "reading": "アフラックスクェア",
377
+ "dict_moras": 9,
378
+ "tokenizer_moras": 8
379
+ }
380
+ ]
381
+ },
382
+ {
383
+ "mora": "グァ",
384
+ "mechanism": "small_vowel_after_a_full_kana",
385
+ "disagreeing_rows_containing_it": 3,
386
+ "agreeing_rows_containing_it": 0,
387
+ "examples": [
388
+ {
389
+ "surface": "グァラニ",
390
+ "reading": "グァラニ",
391
+ "dict_moras": 4,
392
+ "tokenizer_moras": 3
393
+ },
394
+ {
395
+ "surface": "グァラニ",
396
+ "reading": "グァラニ",
397
+ "dict_moras": 4,
398
+ "tokenizer_moras": 3
399
+ },
400
+ {
401
+ "surface": "パラグアイグァラニ",
402
+ "reading": "パラグアイグァラニ",
403
+ "dict_moras": 9,
404
+ "tokenizer_moras": 8
405
+ }
406
+ ]
407
+ },
408
+ {
409
+ "mora": "ジァ",
410
+ "mechanism": "small_vowel_after_a_full_kana",
411
+ "disagreeing_rows_containing_it": 3,
412
+ "agreeing_rows_containing_it": 0,
413
+ "examples": [
414
+ {
415
+ "surface": "ジァン",
416
+ "reading": "ジァン",
417
+ "dict_moras": 3,
418
+ "tokenizer_moras": 2
419
+ },
420
+ {
421
+ "surface": "ジァン・ジァン",
422
+ "reading": "ジァンジァン",
423
+ "dict_moras": 6,
424
+ "tokenizer_moras": 4
425
+ }
426
+ ]
427
+ },
428
+ {
429
+ "mora": "ビィ",
430
+ "mechanism": "small_vowel_after_a_full_kana",
431
+ "disagreeing_rows_containing_it": 3,
432
+ "agreeing_rows_containing_it": 0,
433
+ "examples": [
434
+ {
435
+ "surface": "カービィ",
436
+ "reading": "カービィ",
437
+ "dict_moras": 4,
438
+ "tokenizer_moras": 3
439
+ },
440
+ {
441
+ "surface": "ギャツビィゴルフクラブ",
442
+ "reading": "ギャツビィゴルフクラブ",
443
+ "dict_moras": 10,
444
+ "tokenizer_moras": 9
445
+ },
446
+ {
447
+ "surface": "シューメーカー・レビィ",
448
+ "reading": "シューメーカーレビィ",
449
+ "dict_moras": 9,
450
+ "tokenizer_moras": 8
451
+ }
452
+ ]
453
+ },
454
+ {
455
+ "mora": "ケュ",
456
+ "mechanism": "palatalisation_on_a_non_standard_base",
457
+ "disagreeing_rows_containing_it": 2,
458
+ "agreeing_rows_containing_it": 0,
459
+ "examples": [
460
+ {
461
+ "surface": "寒けい",
462
+ "reading": "サムケュー",
463
+ "dict_moras": 5,
464
+ "tokenizer_moras": 4
465
+ },
466
+ {
467
+ "surface": "鮮らけい",
468
+ "reading": "アザラケュー",
469
+ "dict_moras": 6,
470
+ "tokenizer_moras": 5
471
+ }
472
+ ]
473
+ },
474
+ {
475
+ "mora": "ジィ",
476
+ "mechanism": "small_vowel_after_a_full_kana",
477
+ "disagreeing_rows_containing_it": 2,
478
+ "agreeing_rows_containing_it": 0,
479
+ "examples": [
480
+ {
481
+ "surface": "パンジィ",
482
+ "reading": "パンジィ",
483
+ "dict_moras": 4,
484
+ "tokenizer_moras": 3
485
+ },
486
+ {
487
+ "surface": "ファジィ",
488
+ "reading": "ファジィ",
489
+ "dict_moras": 3,
490
+ "tokenizer_moras": 2
491
+ }
492
+ ]
493
+ },
494
+ {
495
+ "mora": "ヂュ",
496
+ "mechanism": "youon_written_on_the_di_row_historical_orthography",
497
+ "disagreeing_rows_containing_it": 2,
498
+ "agreeing_rows_containing_it": 0,
499
+ "examples": [
500
+ {
501
+ "surface": "ぢゃぢゅぢょ",
502
+ "reading": "ヂャヂュヂョ",
503
+ "dict_moras": 6,
504
+ "tokenizer_moras": 3
505
+ },
506
+ {
507
+ "surface": "ヂャヂュヂョ",
508
+ "reading": "ヂャヂュヂョ",
509
+ "dict_moras": 6,
510
+ "tokenizer_moras": 3
511
+ }
512
+ ]
513
+ },
514
+ {
515
+ "mora": "デェ",
516
+ "mechanism": "small_vowel_after_a_full_kana",
517
+ "disagreeing_rows_containing_it": 2,
518
+ "agreeing_rows_containing_it": 0,
519
+ "examples": [
520
+ {
521
+ "surface": "でぇ",
522
+ "reading": "デェ",
523
+ "dict_moras": 2,
524
+ "tokenizer_moras": 1
525
+ },
526
+ {
527
+ "surface": "デェ",
528
+ "reading": "デェ",
529
+ "dict_moras": 2,
530
+ "tokenizer_moras": 1
531
+ }
532
+ ]
533
+ },
534
+ {
535
+ "mora": "エィ",
536
+ "mechanism": "small_vowel_after_a_full_kana",
537
+ "disagreeing_rows_containing_it": 1,
538
+ "agreeing_rows_containing_it": 0,
539
+ "examples": [
540
+ {
541
+ "surface": "エィンデン",
542
+ "reading": "エィンデン",
543
+ "dict_moras": 5,
544
+ "tokenizer_moras": 4
545
+ }
546
+ ]
547
+ },
548
+ {
549
+ "mora": "ガュ",
550
+ "mechanism": "palatalisation_on_a_non_standard_base",
551
+ "disagreeing_rows_containing_it": 1,
552
+ "agreeing_rows_containing_it": 0,
553
+ "examples": [
554
+ {
555
+ "surface": "凶い",
556
+ "reading": "マガュー",
557
+ "dict_moras": 4,
558
+ "tokenizer_moras": 3
559
+ }
560
+ ]
561
+ },
562
+ {
563
+ "mora": "キィ",
564
+ "mechanism": "small_vowel_after_a_full_kana",
565
+ "disagreeing_rows_containing_it": 1,
566
+ "agreeing_rows_containing_it": 0,
567
+ "examples": [
568
+ {
569
+ "surface": "ラッキィ池田",
570
+ "reading": "ラッキィイケダ",
571
+ "dict_moras": 7,
572
+ "tokenizer_moras": 6
573
+ }
574
+ ]
575
+ },
576
+ {
577
+ "mora": "グゥ",
578
+ "mechanism": "small_vowel_after_a_full_kana",
579
+ "disagreeing_rows_containing_it": 1,
580
+ "agreeing_rows_containing_it": 0,
581
+ "examples": [
582
+ {
583
+ "surface": "アウグゥストゥス",
584
+ "reading": "アウグゥストゥス",
585
+ "dict_moras": 7,
586
+ "tokenizer_moras": 6
587
+ }
588
+ ]
589
+ },
590
+ {
591
+ "mora": "ゲュ",
592
+ "mechanism": "palatalisation_on_a_non_standard_base",
593
+ "disagreeing_rows_containing_it": 1,
594
+ "agreeing_rows_containing_it": 0,
595
+ "examples": [
596
+ {
597
+ "surface": "繁い",
598
+ "reading": "シゲュー",
599
+ "dict_moras": 4,
600
+ "tokenizer_moras": 3
601
+ }
602
+ ]
603
+ },
604
+ {
605
+ "mora": "コァ",
606
+ "mechanism": "small_vowel_after_a_full_kana",
607
+ "disagreeing_rows_containing_it": 1,
608
+ "agreeing_rows_containing_it": 0,
609
+ "examples": [
610
+ {
611
+ "surface": "黄家駒",
612
+ "reading": "コァンジャジュ",
613
+ "dict_moras": 5,
614
+ "tokenizer_moras": 4
615
+ }
616
+ ]
617
+ },
618
+ {
619
+ "mora": "ゴォ",
620
+ "mechanism": "small_vowel_after_a_full_kana",
621
+ "disagreeing_rows_containing_it": 1,
622
+ "agreeing_rows_containing_it": 0,
623
+ "examples": [
624
+ {
625
+ "surface": "ゴォォール",
626
+ "reading": "ゴォォール",
627
+ "dict_moras": 5,
628
+ "tokenizer_moras": 4
629
+ }
630
+ ]
631
+ },
632
+ {
633
+ "mora": "スェ",
634
+ "mechanism": "small_vowel_after_a_full_kana",
635
+ "disagreeing_rows_containing_it": 1,
636
+ "agreeing_rows_containing_it": 0,
637
+ "examples": [
638
+ {
639
+ "surface": "スェーター",
640
+ "reading": "スェーター",
641
+ "dict_moras": 5,
642
+ "tokenizer_moras": 4
643
+ }
644
+ ]
645
+ },
646
+ {
647
+ "mora": "セュ",
648
+ "mechanism": "palatalisation_on_a_non_standard_base",
649
+ "disagreeing_rows_containing_it": 1,
650
+ "agreeing_rows_containing_it": 0,
651
+ "examples": [
652
+ {
653
+ "surface": "狭い",
654
+ "reading": "セュー",
655
+ "dict_moras": 3,
656
+ "tokenizer_moras": 2
657
+ }
658
+ ]
659
+ },
660
+ {
661
+ "mora": "チァ",
662
+ "mechanism": "small_vowel_after_a_full_kana",
663
+ "disagreeing_rows_containing_it": 1,
664
+ "agreeing_rows_containing_it": 0,
665
+ "examples": [
666
+ {
667
+ "surface": "江蘇",
668
+ "reading": "チァンスー",
669
+ "dict_moras": 5,
670
+ "tokenizer_moras": 4
671
+ }
672
+ ]
673
+ },
674
+ {
675
+ "mora": "テェ",
676
+ "mechanism": "small_vowel_after_a_full_kana",
677
+ "disagreeing_rows_containing_it": 1,
678
+ "agreeing_rows_containing_it": 0,
679
+ "examples": [
680
+ {
681
+ "surface": "いたい",
682
+ "reading": "イテェ",
683
+ "dict_moras": 3,
684
+ "tokenizer_moras": 2
685
+ }
686
+ ]
687
+ },
688
+ {
689
+ "mora": "ネュ",
690
+ "mechanism": "palatalisation_on_a_non_standard_base",
691
+ "disagreeing_rows_containing_it": 1,
692
+ "agreeing_rows_containing_it": 0,
693
+ "examples": [
694
+ {
695
+ "surface": "おっかねい",
696
+ "reading": "オッカネュー",
697
+ "dict_moras": 6,
698
+ "tokenizer_moras": 5
699
+ }
700
+ ]
701
+ },
702
+ {
703
+ "mora": "フョ",
704
+ "mechanism": "palatalisation_on_a_non_standard_base",
705
+ "disagreeing_rows_containing_it": 1,
706
+ "agreeing_rows_containing_it": 0,
707
+ "examples": [
708
+ {
709
+ "surface": "フョードロフ",
710
+ "reading": "フョードロフ",
711
+ "dict_moras": 6,
712
+ "tokenizer_moras": 5
713
+ }
714
+ ]
715
+ },
716
+ {
717
+ "mora": "ムュ",
718
+ "mechanism": "palatalisation_on_a_non_standard_base",
719
+ "disagreeing_rows_containing_it": 1,
720
+ "agreeing_rows_containing_it": 0,
721
+ "examples": [
722
+ {
723
+ "surface": "薄ら眠い",
724
+ "reading": "ウスラネムュー",
725
+ "dict_moras": 7,
726
+ "tokenizer_moras": 6
727
+ }
728
+ ]
729
+ },
730
+ {
731
+ "mora": "モュ",
732
+ "mechanism": "palatalisation_on_a_non_standard_base",
733
+ "disagreeing_rows_containing_it": 1,
734
+ "agreeing_rows_containing_it": 0,
735
+ "examples": [
736
+ {
737
+ "surface": "パンケモュウパロ川",
738
+ "reading": "パンケモュウパロガワ",
739
+ "dict_moras": 10,
740
+ "tokenizer_moras": 9
741
+ }
742
+ ]
743
+ },
744
+ {
745
+ "mora": "ルュ",
746
+ "mechanism": "palatalisation_on_a_non_standard_base",
747
+ "disagreeing_rows_containing_it": 1,
748
+ "agreeing_rows_containing_it": 0,
749
+ "examples": [
750
+ {
751
+ "surface": "アルュメ",
752
+ "reading": "アルュメ",
753
+ "dict_moras": 4,
754
+ "tokenizer_moras": 3
755
+ }
756
+ ]
757
+ }
758
+ ],
759
+ "mechanism_groups": {
760
+ "palatalisation_on_a_non_standard_base": {
761
+ "pairs": [
762
+ "イュ",
763
+ "ガュ",
764
+ "ケュ",
765
+ "ゲュ",
766
+ "セュ",
767
+ "ナュ",
768
+ "ネュ",
769
+ "フュ",
770
+ "フョ",
771
+ "ムュ",
772
+ "モュ",
773
+ "ルュ"
774
+ ],
775
+ "mismatch_rows_touched": 93
776
+ },
777
+ "small_vowel_after_a_full_kana": {
778
+ "pairs": [
779
+ "エィ",
780
+ "キィ",
781
+ "クァ",
782
+ "クィ",
783
+ "クェ",
784
+ "クォ",
785
+ "グァ",
786
+ "グゥ",
787
+ "コァ",
788
+ "ゴォ",
789
+ "シィ",
790
+ "ジァ",
791
+ "ジィ",
792
+ "スェ",
793
+ "チァ",
794
+ "テェ",
795
+ "デェ",
796
+ "ビィ"
797
+ ],
798
+ "mismatch_rows_touched": 41
799
+ },
800
+ "youon_written_on_the_di_row_historical_orthography": {
801
+ "pairs": [
802
+ "ヂャ",
803
+ "ヂュ",
804
+ "ヂョ"
805
+ ],
806
+ "mismatch_rows_touched": 12
807
+ }
808
+ },
809
+ "surface_script_of_disagreeing_entries": {
810
+ "kana_only": 110,
811
+ "contains_kanji": 27,
812
+ "contains_latin": 4
813
+ }
814
+ },
815
+ "nucleus_within_tokenizer_mora_count": {
816
+ "note": "sanity check only; NAIST accmora is self-consistent by construction",
817
+ "n": 788331,
818
+ "in_range": 788331,
819
+ "rate": 1.0
820
+ }
821
+ },
822
+ "unidic": {
823
+ "mode": "sys.dic",
824
+ "source": "UniDic 2.1.2 (unidic-mecab)",
825
+ "check": "indirect BOUND, not an equality: UniDic records no mora count, so the test is 0 <= aType <= mora_count(reading). It detects under-counting and is blind to over-counting.",
826
+ "devoicing_marks_stripped": [
827
+ "’",
828
+ "'"
829
+ ],
830
+ "entries_with_accent": 751705,
831
+ "accent_annotations": 901116,
832
+ "within_bound_using_surface_reading": 900945,
833
+ "within_bound_rate_surface_reading": 0.9998102353082178,
834
+ "out_of_bound_using_surface_reading": 171,
835
+ "explained_by_lemma_length": {
836
+ "note": "UniDic states aType for the lemma; an inflected surface form is shorter than its own lemma. Re-checking against pronBase absorbs these.",
837
+ "count": 95,
838
+ "by_pos": {
839
+ "動詞-一般": 93,
840
+ "形容詞-一般": 2
841
+ }
842
+ },
843
+ "residual_not_attributable_to_the_tokenizer": {
844
+ "note": "the recorded aType exceeds the mora count of BOTH reading fields in the same row, so no segmentation of that row's own text can satisfy it; these are annotation slips in the source dictionary",
845
+ "count": 76,
846
+ "rate_of_all_annotations": 8.43398630143067e-05,
847
+ "by_pos": {
848
+ "動詞-一般": 39,
849
+ "名詞-普通名詞": 19,
850
+ "名詞-固有名詞": 11,
851
+ "名詞-数詞": 4,
852
+ "副詞-*": 3
853
+ },
854
+ "examples": [
855
+ {
856
+ "orth": "すま",
857
+ "pron": "スマ",
858
+ "pron_base": "スマ",
859
+ "recorded_aType": 4,
860
+ "tokenizer_moras_pron": 2,
861
+ "tokenizer_moras_lemma": 2,
862
+ "pos": "名詞-普通名詞"
863
+ },
864
+ {
865
+ "orth": "ひ",
866
+ "pron": "ヒ",
867
+ "pron_base": "ヒ",
868
+ "recorded_aType": 2,
869
+ "tokenizer_moras_pron": 1,
870
+ "tokenizer_moras_lemma": 1,
871
+ "pos": "名詞-数詞"
872
+ },
873
+ {
874
+ "orth": "ふ",
875
+ "pron": "フ",
876
+ "pron_base": "フ",
877
+ "recorded_aType": 2,
878
+ "tokenizer_moras_pron": 1,
879
+ "tokenizer_moras_lemma": 1,
880
+ "pos": "名詞-数詞"
881
+ },
882
+ {
883
+ "orth": "ぽおん",
884
+ "pron": "ポーン",
885
+ "pron_base": "ポーン",
886
+ "recorded_aType": 4,
887
+ "tokenizer_moras_pron": 3,
888
+ "tokenizer_moras_lemma": 3,
889
+ "pos": "副詞-*"
890
+ },
891
+ {
892
+ "orth": "ぽーん",
893
+ "pron": "ポーン",
894
+ "pron_base": "ポーン",
895
+ "recorded_aType": 4,
896
+ "tokenizer_moras_pron": 3,
897
+ "tokenizer_moras_lemma": 3,
898
+ "pos": "副詞-*"
899
+ },
900
+ {
901
+ "orth": "アテュス",
902
+ "pron": "アチュス",
903
+ "pron_base": "アチュス",
904
+ "recorded_aType": 10,
905
+ "tokenizer_moras_pron": 3,
906
+ "tokenizer_moras_lemma": 3,
907
+ "pos": "名詞-固有名詞"
908
+ },
909
+ {
910
+ "orth": "ウヂノワキ",
911
+ "pron": "ウジノワキ",
912
+ "pron_base": "ウジノワキ",
913
+ "recorded_aType": 7,
914
+ "tokenizer_moras_pron": 5,
915
+ "tokenizer_moras_lemma": 5,
916
+ "pos": "名詞-固有名詞"
917
+ },
918
+ {
919
+ "orth": "エレクトロ",
920
+ "pron": "エレクトロ",
921
+ "pron_base": "エレクトロ",
922
+ "recorded_aType": 8,
923
+ "tokenizer_moras_pron": 5,
924
+ "tokenizer_moras_lemma": 5,
925
+ "pos": "名詞-普通名詞"
926
+ },
927
+ {
928
+ "orth": "サラン",
929
+ "pron": "サラン",
930
+ "pron_base": "サラン",
931
+ "recorded_aType": 4,
932
+ "tokenizer_moras_pron": 3,
933
+ "tokenizer_moras_lemma": 3,
934
+ "pos": "名詞-固有名詞"
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+ },
936
+ {
937
+ "orth": "スマ",
938
+ "pron": "スマ",
939
+ "pron_base": "スマ",
940
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+ "tokenizer_moras_pron": 2,
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+ "tokenizer_moras_lemma": 2,
943
+ "pos": "名詞-普通名詞"
944
+ },
945
+ {
946
+ "orth": "スルホ",
947
+ "pron": "スルホ",
948
+ "pron_base": "スルホ",
949
+ "recorded_aType": 4,
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951
+ "tokenizer_moras_lemma": 3,
952
+ "pos": "名詞-普通名詞"
953
+ },
954
+ {
955
+ "orth": "トム",
956
+ "pron": "トム",
957
+ "pron_base": "トム",
958
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+ "tokenizer_moras_lemma": 2,
961
+ "pos": "名詞-普通名詞"
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+ },
963
+ {
964
+ "orth": "ドゥバイ",
965
+ "pron": "ドゥバイ",
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+ "pron_base": "ドゥバイ",
967
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+ "tokenizer_moras_lemma": 3,
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+ "pos": "名詞-固有名詞"
971
+ },
972
+ {
973
+ "orth": "バンデグラフ",
974
+ "pron": "バンデグラフ",
975
+ "pron_base": "バンデグラフ",
976
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+ "pos": "名詞-普通名詞"
980
+ },
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+ {
982
+ "orth": "フェデラル",
983
+ "pron": "フェデラル",
984
+ "pron_base": "フェデラル",
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+ },
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991
+ "orth": "プレスト",
992
+ "pron": "プレスト",
993
+ "pron_base": "プレスト",
994
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997
+ "pos": "名詞-普通名詞"
998
+ },
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+ {
1000
+ "orth": "ペブル",
1001
+ "pron": "ペブル",
1002
+ "pron_base": "ペブル",
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+ "tokenizer_moras_lemma": 3,
1006
+ "pos": "名詞-固有名詞"
1007
+ },
1008
+ {
1009
+ "orth": "ペント",
1010
+ "pron": "ペント",
1011
+ "pron_base": "ペント",
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+ "tokenizer_moras_lemma": 3,
1015
+ "pos": "名詞-普通名詞"
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+ },
1017
+ {
1018
+ "orth": "ポーン",
1019
+ "pron": "ポーン",
1020
+ "pron_base": "ポーン",
1021
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1023
+ "tokenizer_moras_lemma": 3,
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+ "pos": "副詞-*"
1025
+ },
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+ {
1027
+ "orth": "マーシュ",
1028
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1029
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1030
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+ },
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1036
+ "orth": "ミクー",
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+ "pron": "ミクー",
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+ "pos": "名詞-固有名詞"
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+ },
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+ {
1045
+ "orth": "ラオアグ",
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+ "pron": "ラオアグ",
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+ },
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+ {
1054
+ "orth": "リンチ",
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+ "pron_base": "リンチ",
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+ },
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1063
+ "orth": "レッセ",
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+ },
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+ {
1072
+ "orth": "ワクスマン",
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+ "pron": "ワクスマン",
1074
+ "pron_base": "ワクスマン",
1075
+ "recorded_aType": 11,
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1078
+ "pos": "名詞-固有名詞"
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+ }
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+ ]
1081
+ }
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+ }
1083
+ }
stats.json ADDED
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+ "note": "gold_accents is a SET: >1 entry means the dictionaries attest more than one accent. No human annotation is present in this release."
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test.jsonl ADDED
The diff for this file is too large to render. See raw diff
 
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