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The dataset generation failed
Error code:   DatasetGenerationError
Exception:    CastError
Message:      Couldn't cast
languages: struct<aaa: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_t (... 117931 chars omitted)
  child 0, aaa: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 1, aai: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 2, aak: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 3, aau: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 4, aaz: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_su
...
_suffixes: int64
      child 4, n_types: int64
  child 1099, ztq: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 1100, zts: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 1101, zty: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
  child 1102, zyp: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
      child 0, content_sha256: string
      child 1, n_prefixes: int64
      child 2, n_stems: int64
      child 3, n_suffixes: int64
      child 4, n_types: int64
schema: struct<prefixes: string, stems: string, suffixes: string>
  child 0, prefixes: string
  child 1, stems: string
  child 2, suffixes: string
suffixes: list<item: string>
  child 0, item: string
prefixes: list<item: string>
  child 0, item: string
n_types: int64
stems: list<item: string>
  child 0, item: string
to
{'suffixes': List(Value('string')), 'prefixes': List(Value('string')), 'n_types': Value('int64'), 'stems': List(Value('string'))}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1827, in _prepare_split_single
                  for key, table in generator:
                                    ^^^^^^^^^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 613, in wrapped
                  for item in generator(*args, **kwargs):
                              ~~~~~~~~~^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 343, in _generate_tables
                  self._cast_table(pa_table, json_field_paths=json_field_paths),
                  ~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/packaged_modules/json/json.py", line 132, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2378, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/usr/local/lib/python3.14/site-packages/datasets/table.py", line 2306, in cast_table_to_schema
                  raise CastError(
                  ...<3 lines>...
                  )
              datasets.table.CastError: Couldn't cast
              languages: struct<aaa: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_t (... 117931 chars omitted)
                child 0, aaa: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 1, aai: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 2, aak: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 3, aau: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 4, aaz: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_su
              ...
              _suffixes: int64
                    child 4, n_types: int64
                child 1099, ztq: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 1100, zts: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 1101, zty: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
                child 1102, zyp: struct<content_sha256: string, n_prefixes: int64, n_stems: int64, n_suffixes: int64, n_types: int64>
                    child 0, content_sha256: string
                    child 1, n_prefixes: int64
                    child 2, n_stems: int64
                    child 3, n_suffixes: int64
                    child 4, n_types: int64
              schema: struct<prefixes: string, stems: string, suffixes: string>
                child 0, prefixes: string
                child 1, stems: string
                child 2, suffixes: string
              suffixes: list<item: string>
                child 0, item: string
              prefixes: list<item: string>
                child 0, item: string
              n_types: int64
              stems: list<item: string>
                child 0, item: string
              to
              {'suffixes': List(Value('string')), 'prefixes': List(Value('string')), 'n_types': Value('int64'), 'stems': List(Value('string'))}
              because column names don't match
              
              The above exception was the direct cause of the following exception:
              
              Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 1369, in compute_config_parquet_and_info_response
                  parquet_operations, partial, estimated_dataset_info = stream_convert_to_parquet(
                                                                        ~~~~~~~~~~~~~~~~~~~~~~~~~^
                      builder, max_dataset_size_bytes=max_dataset_size_bytes
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  )
                  ^
                File "/src/services/worker/src/worker/job_runners/config/parquet_and_info.py", line 948, in stream_convert_to_parquet
                  builder._prepare_split(split_generator=splits_generators[split], file_format="parquet")
                  ~~~~~~~~~~~~~~~~~~~~~~^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1694, in _prepare_split
                  for job_id, done, content in self._prepare_split_single(
                                               ~~~~~~~~~~~~~~~~~~~~~~~~~~^
                      gen_kwargs=gen_kwargs, job_id=job_id, **_prepare_split_args
                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
                  ):
                  ^
                File "/usr/local/lib/python3.14/site-packages/datasets/builder.py", line 1880, in _prepare_split_single
                  raise DatasetGenerationError("An error occurred while generating the dataset") from e
              datasets.exceptions.DatasetGenerationError: An error occurred while generating the dataset

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suffixes
list
prefixes
list
n_types
int64
stems
list
[ "a", "i", "ẹ", "e", "hi", "ọ", "hẹ", "ha", "o", "ia", "gha", "u", "ahẹ", "hia", "be", "gbe", "hahẹ", "he", "nha", "nhi", "re", "agha", "mhi", "si", "va", "iẹ", "egbe", "họ", "mhẹ", "ghi", "nọ", "inhi", "ti", "hiẹ", "mha", "ma", "nhẹ", "bọ", ...
[ "nh", "kh", "gh", "im", "ik", "kp", "ọnh", "omh", "fi", "ny", "it", "om", "ij", "ir", "gb", "mh", "wh", "ọm", "ọnhọ", "re", "ig", "yh", "nhọ", "il", "ak", "ọk", "ikp", "imh", "is", "ag", "ru", "el", "agb", "omhi", "vb", "khu", "id", "sa", "...
3,309
[ "isẹzọ", "oti", "itamhughele", "idaniẹli", "zhamhẹ", "ghob", "iram", "inhẹ", "ijoko", "ihẹrapolisi", "wiaku", "avọẹ", "ẹẹnw", "ghona", "dada", "whia", "itẹtiusi", "khooudo", "imuegbe", "khanhakọ", "atiọki", "emọhi", "ipam", "aasa", "zaghahẹgha", "yhọ", "nuhu", "...
[ "n", "ih", "h", "i", "r", "a", "u", "t", "mih", "amaim", "amih", "in", "en", "an", "maim", "w", "b", "it", "y", "imih", "uw", "ar", "m", "iy", "ir", "ah", "yan", "e", "ra", "ne", "rih", "namih", "aim", "ane", "wih", "un", "nih", "ayan", "uw...
[ "hi", "kwa", "na", "ta", "kw", "hin", "kwan", "in", "hina", "an", "kwana", "ina", "ku", "tan", "ba", "hit", "hib", "te", "ana", "bai", "ni", "eb", "ab", "ti", "tana", "bi", "nab", "kwani", "hita", "ebi", "hini", "kwab", "at", "ka", "hibi", "it", ...
10,229
[ "nibibabatun", "kwaneya", "taras", "sese", "tanabata", "himamataren", "tebiyafar", "natabiri", "hiorereb", "masawa", "ataba", "roumutufuren", "abobosemor", "sawusawuwih", "ya", "inaka", "kwiyoun", "baisesebar", "kubobobe", "ukwa", "ruburubu", "namamaririb", "hosea", "ta...
["ɨ","rɨnɨ","nɨ","o","ɨnɨ","á","rɨ","yɨ","a","pɨ","mɨ","ɨrɨ","ɨrɨnɨ","árɨnɨ","ro"(...TRUNCATED)
["nɨ","wi","sea","rɨ","mɨ","nea","ne","se","ur","ni","imón","me","ya","imó","seai","wɨ","im","(...TRUNCATED)
22,176
["niaíwen","tɨgɨíwa","yipɨrɨár","wɨnowárɨwanigɨnɨ","ŋwɨápɨ","wépámɨ","eánɨŋor(...TRUNCATED)
["n","r","a","k","e","y","ay","w","on","s","i","aw","an","o","p","h","ok","uw","iy","ow","yay","or",(...TRUNCATED)
["sa","lo","so","swa","ma","ok","no","na","ka","lok","on","ko","ho","lon","po","la","li","me","ey","(...TRUNCATED)
2,423
["kanda","lwos","leysay","huono","loparoway","wouknowsi","hesekia","wowr","pukyay","kriykriy","poh",(...TRUNCATED)
["n","ꞌ","k","t","in","an","s","i","aꞌ","un","f","u","e","r","en","b","m","o","a","on","iꞌ","e(...TRUNCATED)
["na","an","am","mi","ma","mu","aꞌ","ta","naꞌ","at","nm","anm","nt","nma","anma","ns","ant","nat(...TRUNCATED)
9,043
["mitoꞌ","purtik","anro","kahuꞌ","ꞌromi","feꞌen","korasin","uꞌa","harinet","efrata","namre(...TRUNCATED)
["n","aꞌ","an","y","a","un","naꞌ","ay","u","g","ng","anaꞌ","i","in","ꞌ","uy","t","aku","ga(...TRUNCATED)
["ma","na","pa","ka","nag","mag","nan","in","pag","ba","maka","man","impa","ta","ha","naka","mak","p(...TRUNCATED)
3,440
["nagp","ukasyun","nêdên","pabang","malêng","makah","grupun","liyaki","palatêng","dumahuy","naka(...TRUNCATED)
["ɛ","ʋ","ɩ","nɩ","nί","ε","a","ί","u","i","ní","ɔ","e","mʋ","n","í","ni","ɛnɛ","ʋɛ",(...TRUNCATED)
["nʋ","nɩ","nɔ","ni","fʋ","fɩ","na","ne","nu","mʋ","fɔ","yɔ","rʋ","fi","mɩ","no","rɩ","n(...TRUNCATED)
9,864
["nɩyɩyɩn","nɩkpran","ʋkʋan","yɔkpʋmʋ","fidelilet","mʋgʋgɔfʋ","ɩlɩmʋ","akilas","nέd(...TRUNCATED)
["a","ɔ","ɛ","ga","m","g","l","ra","am","b","ma","ng","i","e","n","na","nɔ","gɔ","ba","lɔ","gɛ(...TRUNCATED)
["ak","at","ab","ay","ar","ɛk","li","nt","nk","akp","aj","as","an","al","ny","af","ɛb","ag","ba","(...TRUNCATED)
2,289
["bɛtsayida","akpena","mfɔnɛ","ɔyem","tobe","ɛwɔ","ɔgb","akukun","pɔntus","ayab","aribi","af(...TRUNCATED)
["om","a","i","m","an","n","gh","e","h","l","iom","naan","r","ghi","am","ogh","o","ph","u","aan","hi(...TRUNCATED)
["rꞌ","rꞌa","ka","kạ","mꞌ","ko","ro","ke","ra","kọ","kẹ","rạ","rọ","re","ma","kꞌ",(...TRUNCATED)
24,124
["mamune","ekoo","ụkaanaan","mạatarion","ọonha","kodoghom","ẹleke","rꞌiizin","mewunaan","k(...TRUNCATED)
["an","n","a","o","i","on","y","en","t","h","ay","g","in","nan","na","at","ng","l","ang","tan","wa",(...TRUNCATED)
["ma","na","pa","ampa","am","ka","pan","man","amp","nan","mang","in","angka","pina","ampan","mak","p(...TRUNCATED)
8,558
["kabekahan","nakihabi","pagkalamo","ampaytongtong","ampanipon","dinih","ladak","bawon","pahinga","b(...TRUNCATED)
End of preview.

target-morphology

Per-language unsupervised morphology models — productive suffixes, prefixes, and a stem lexicon, each learned MDL-free ("Linguistica"-style: a suffix is productive if it attaches to many paradigm stems) from that language's own Bible text. No labels, no pretrained model, no download — so it runs on any language with a translation, including those with zero LLM/encoder coverage.

stem(word) strips one productive affix when the remainder is a known stem; inflected variants collapse to a shared stem (e.g. Hindi बोला/बोलता → बोल). Built for the lexeme-aligner (it fills gloss's normalizer and optionally stems eflomal's input), but published standalone because unsupervised segmentation is reusable.

CC0-1.0 — models are derived statistics (affix inventories + stem lists), no source text redistributed. See manifest.json for per-language stats + content hashes.

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