pretty_name: MorphBench (German)
language:
- de
license: cc-by-sa-4.0
tags:
- morphology
- tokenization
- evaluation
- german
dataset_info:
- config_name: task1_inflection
features:
- name: lemma
dtype: string
- name: feats
dtype: string
- name: target
dtype: string
- name: status
dtype: string
splits:
- name: train
num_bytes: 835801
num_examples: 11982
- name: dev
num_bytes: 69889
num_examples: 995
- name: test
num_bytes: 138820
num_examples: 1989
- name: test_rare
num_bytes: 36938
num_examples: 499
- name: test_memorization
num_bytes: 32659
num_examples: 498
download_size: 393231
dataset_size: 1114107
- config_name: task2_deriv_segmentation
features:
- name: word
dtype: string
- name: segmentation
dtype: string
- name: status
dtype: string
splits:
- name: train
num_bytes: 583722
num_examples: 10000
- name: dev
num_bytes: 59481
num_examples: 1000
- name: test_main
num_bytes: 118920
num_examples: 1966
- name: test_memorization
num_bytes: 28135
num_examples: 500
- name: test_oov
num_bytes: 31843
num_examples: 500
download_size: 348072
dataset_size: 822101
- config_name: task3_derivation
features:
- name: base
dtype: string
- name: affix
dtype: string
- name: target
dtype: string
- name: status
dtype: string
splits:
- name: train
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num_examples: 9935
- name: dev
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num_examples: 998
- name: test_main
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num_examples: 1992
- name: test_memorization
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num_examples: 494
- name: test_oov
num_bytes: 33410
num_examples: 500
download_size: 331468
dataset_size: 861717
- config_name: task4_compound
features:
- name: word
dtype: string
- name: segmentation
dtype: string
- name: difficulty
dtype: string
- name: source
dtype: string
splits:
- name: train
num_bytes: 573352
num_examples: 9982
- name: dev
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num_examples: 997
- name: test_main
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num_examples: 2000
- name: test_rare
num_bytes: 6426
num_examples: 117
- name: test_memorization
num_bytes: 30049
num_examples: 499
- name: test_hardest
num_bytes: 30053
num_examples: 495
download_size: 437099
dataset_size: 806310
- config_name: task5_affix_function
features:
- name: word
dtype: string
- name: function
dtype: string
- name: freq
dtype: int64
- name: status
dtype: string
splits:
- name: train
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num_examples: 5462
- name: dev
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num_examples: 747
- name: test
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num_examples: 1552
download_size: 108713
dataset_size: 491093
- config_name: task6a_definition
features:
- name: word
dtype: string
- name: gloss
dtype: string
- name: base
dtype: string
- name: affix
dtype: string
- name: function
dtype: string
- name: derived_freq
dtype: int64
- name: base_exposure
dtype: int64
- name: status
dtype: string
splits:
- name: train
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num_examples: 9131
- name: dev
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num_examples: 1251
- name: test_main
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num_examples: 327
- name: test_main_oov
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num_examples: 480
- name: test_rare
num_bytes: 51435
num_examples: 379
- name: test_memorization
num_bytes: 144907
num_examples: 1022
download_size: 946934
dataset_size: 1717471
- config_name: task6b_definition_mcq
features:
- name: word
dtype: string
- name: base
dtype: string
- name: affix
dtype: string
- name: function
dtype: string
- name: gold_gloss
dtype: string
- name: distractors
sequence: string
- name: pretrain_status
dtype: string
- name: derived_freq
dtype: int64
- name: base_exposure
dtype: int64
splits:
- name: dev
num_bytes: 580104
num_examples: 1242
- name: main
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num_examples: 324
- name: main_oov
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num_examples: 473
- name: rare
num_bytes: 178322
num_examples: 375
- name: memorization
num_bytes: 480506
num_examples: 1013
download_size: 767173
dataset_size: 1616150
configs:
- config_name: task1_inflection
data_files:
- split: train
path: task1_inflection/train-*
- split: dev
path: task1_inflection/dev-*
- split: test
path: task1_inflection/test-*
- split: test_rare
path: task1_inflection/test_rare-*
- split: test_memorization
path: task1_inflection/test_memorization-*
- config_name: task2_deriv_segmentation
data_files:
- split: train
path: task2_deriv_segmentation/train-*
- split: dev
path: task2_deriv_segmentation/dev-*
- split: test_main
path: task2_deriv_segmentation/test_main-*
- split: test_memorization
path: task2_deriv_segmentation/test_memorization-*
- split: test_oov
path: task2_deriv_segmentation/test_oov-*
- config_name: task3_derivation
data_files:
- split: train
path: task3_derivation/train-*
- split: dev
path: task3_derivation/dev-*
- split: test_main
path: task3_derivation/test_main-*
- split: test_memorization
path: task3_derivation/test_memorization-*
- split: test_oov
path: task3_derivation/test_oov-*
- config_name: task4_compound
data_files:
- split: train
path: task4_compound/train-*
- split: dev
path: task4_compound/dev-*
- split: test_main
path: task4_compound/test_main-*
- split: test_rare
path: task4_compound/test_rare-*
- split: test_memorization
path: task4_compound/test_memorization-*
- split: test_hardest
path: task4_compound/test_hardest-*
- config_name: task5_affix_function
data_files:
- split: train
path: task5_affix_function/train-*
- split: dev
path: task5_affix_function/dev-*
- split: test
path: task5_affix_function/test-*
- config_name: task6a_definition
data_files:
- split: train
path: task6a_definition/train-*
- split: dev
path: task6a_definition/dev-*
- split: test_main
path: task6a_definition/test_main-*
- split: test_main_oov
path: task6a_definition/test_main_oov-*
- split: test_rare
path: task6a_definition/test_rare-*
- split: test_memorization
path: task6a_definition/test_memorization-*
- config_name: task6b_definition_mcq
data_files:
- split: dev
path: task6b_definition_mcq/dev-*
- split: main
path: task6b_definition_mcq/main-*
- split: main_oov
path: task6b_definition_mcq/main_oov-*
- split: rare
path: task6b_definition_mcq/rare-*
- split: memorization
path: task6b_definition_mcq/memorization-*
- config_name: verb_cloze
data_files:
- split: train
path: verb_cloze/train.jsonl
- split: validation
path: verb_cloze/validation.jsonl
- split: test
path: verb_cloze/test.jsonl
- split: test_rare
path: verb_cloze/test_rare.jsonl
MorphBench — German Morphology Evaluation Suite
A benchmark for morphology-aware tokenizers and language models in German. Eight numbered tasks probe inflection, segmentation, derivation, compounding, affix semantics, and whole-word meaning. Each task is a config; difficulty/generalization tiers are splits.
from datasets import load_dataset
ds = load_dataset("yuanxin112/morphbench-de", "task3_derivation", split="test_main")
Tasks
task1_inflection
Produce the inflected form from a lemma + features.
input interagieren + v;ind;pl;1;pst → output interagierten
columns: lemma, feats, target, status
task2_deriv_segmentation — derivational segmentation
Split a derived word into base + affix.
input Dreher → output drehen|er
columns: word, segmentation, status
task3_derivation
Build the derived word from a base + affix.
input Apotheke + pflichtig → output apothekenpflichtig
columns: base, affix, target, status
task4_compound
Split a compound into its parts.
input Freiheitsheld → output Freiheit|Held
columns: word, segmentation, difficulty, source
task5_affix_function
Given a derived word, classify the semantic function of its affix (13 classes:
negation, without, agent_person, make_become, …).
input stimmlos → output without
columns: word, function, freq, status
task6a_definition
Generate the dictionary gloss of a derived word.
input Malocher → output Arbeitnehmer, der überwiegend körperlich hart … arbeitet
columns: word, gloss, base, affix, function, derived_freq, base_exposure, status
task6b_definition_mcq
Multiple-choice version of 6a: pick the correct gloss among hard distractors.
columns: word, base, affix, function, gold_gloss, distractors, pretrain_status, derived_freq, base_exposure
Splits — how items are bucketed
Every test split is defined by the pretraining exposure of the item's parts
(frequency in the BabyLM-style German training corpus): seen = frequency above a
threshold, unseen = frequency 0. The headline idea everywhere is the target is
UNSEEN while its base/lemma IS seen (compositional generalization); memorization
and rare/OOV/hardest are the seen / harder controls. train, dev are
training / validation.
task1_inflection — by (lemma seen?) × (this form seen?):
| split | condition |
|---|---|
test (main) |
lemma seen, form unseen |
test_memorization |
lemma seen, form seen |
test_rare |
lemma unseen, form unseen |
task2_deriv_segmentation, task3_derivation — by (base seen?) × (derived seen?), where seen = corpus freq ≥ 1:
| split | condition |
|---|---|
test_main |
base seen, derived unseen (compositional generalization) |
test_memorization |
base seen, derived seen |
test_OOV |
base unseen, derived unseen |
task4_compound — by (compound word seen?) × (all components seen?), where compound seen = freq ≥ 1 and a component is seen = freq ≥ 5:
| split | condition | what it tests |
|---|---|---|
test_main |
compound unseen, all components seen | compositional generalization |
test_memorization |
compound seen, all components seen | rote recall |
test_rare |
compound seen, some component rare | mixed |
test_hardest |
compound unseen, some component unseen | hardest |
task6a_definition, task6b_definition_mcq — by the derived word's corpus frequency derived_freq, splitting the unseen case by base_exposure:
| split | condition |
|---|---|
memorization |
derived_freq ≥ 20 |
rare |
derived_freq 1–5 |
main |
derived_freq = 0 and base_exposure ≥ 300 (base familiar) |
main_oov |
derived_freq = 0 and base_exposure < 300 (base also OOV) |
task5_affix_function uses a plain train / dev / test split (no difficulty buckets). The status / pretrain_cell column on each row
records the exposure cell directly, e.g. base_seen+derived_unseen, lem_seen+form_unseen.
Note: the German "seen" thresholds are lower than the English suite (derivation/ segmentation use freq ≥ 1; definition uses
derived_freq ≥ 20,base_exposure ≥ 300).
Provenance
Built from German Wiktionary (via kaikki.org / wiktextract) and UniMorph.
Companion lexical resource: yuanxin112/wiktionary-morph.
English counterpart: yuanxin112/morphbench-en.
License
Derived from Wiktionary — CC BY-SA 4.0; attribute Wiktionary and its contributors.
verb_cloze — Contextual Verb-Inflection Cloze (added config)
Leave-one-out cloze: given a verb lemma, partial feats (one morphological
dimension withheld), and a natural sentence with the target verb replaced by a
blank marker, generate the inflected form. Splits are lemma-disjoint.
Sentences come from Universal Dependencies treebanks (a derivative; CC BY-SA
4.0 — verify per-treebank licenses, e.g. English ParTUT is CC BY-NC-SA).
from datasets import load_dataset
ds = load_dataset("yuanxin112/morphbench-de", "verb_cloze")