Dataset Viewer
Auto-converted to Parquet Duplicate
lexeme
string
stem
string
sense
string
surface
string
count
int32
share
float32
method
string
source_corpus
string
base_text
string
hbo:0001
1
naiꞌ
63
0.3559
gloss
WLC
aaz_C01
hbo:0001
1
amaꞌ
55
0.3107
gloss
WLC
aaz_C01
hbo:0001
1
amaꞌ
32
0.1988
eflomal
WLC
aaz_C01
hbo:0001
1
aamf ee
22
0.1366
eflomal
WLC
aaz_C01
hbo:0001
1
amaf
21
0.1186
gloss
WLC
aaz_C01
hbo:0001
1
aam
19
0.1073
gloss
WLC
aaz_C01
hbo:0001
1
amaf
18
0.1118
eflomal
WLC
aaz_C01
hbo:0001
1
aamf ee
15
0.0847
gloss
WLC
aaz_C01
hbo:0001
1
aam
10
0.0621
eflomal
WLC
aaz_C01
hbo:0001
1
naiꞌ
10
0.0621
eflomal
WLC
aaz_C01
hbo:0001
1
amaꞌ in
7
0.0435
eflomal
WLC
aaz_C01
hbo:0001
1
in aamf ee
5
0.0311
eflomal
WLC
aaz_C01
hbo:0001
1
hit amaꞌ
5
0.0311
eflomal
WLC
aaz_C01
hbo:0001
1
in
4
0.0248
eflomal
WLC
aaz_C01
hbo:0001
1
ho amaꞌ
4
0.0248
eflomal
WLC
aaz_C01
hbo:0001
1
in amaf
4
0.0248
eflomal
WLC
aaz_C01
hbo:0001
1
unuꞌ
3
0.0186
eflomal
WLC
aaz_C01
hbo:0001
1
beꞌi naꞌi
3
0.0186
eflomal
WLC
aaz_C01
hbo:0001
1
ee
2
0.0124
eflomal
WLC
aaz_C01
hbo:0001
1
naꞌi
2
0.0124
eflomal
WLC
aaz_C01
hbo:0001
1
mfain
2
0.0124
eflomal
WLC
aaz_C01
hbo:0001
1
yakop
2
0.0124
eflomal
WLC
aaz_C01
hbo:0001
1
nain
2
0.0113
gloss
WLC
aaz_C01
hbo:0001
1
atuuk
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
amaf nmoin
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
sufam
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
aam honif
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
ben
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
kai amaꞌ
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
in aam
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
noik aamf ee
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
naꞌi in
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
ꞌuum
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
amaꞌ naꞌbees
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
nasaeb
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
ho amaꞌ naꞌbees
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
kuan ee
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
manekam
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
in aamf ee in
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
amaꞌ nmoin
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
ee amaꞌ
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
amaꞌ anreek
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
amaꞌ ansuus
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
ho amaꞌ naꞌbees neu unuꞌ
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
aam amaꞌ
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
nait
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
aamf
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
naꞌbees
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
tataf
1
0.0062
eflomal
WLC
aaz_C01
hbo:0001
1
ꞌtaam
1
0.0056
gloss
WLC
aaz_C01
hbo:0001
1
nai
1
0.0056
gloss
WLC
aaz_C01
hbo:0014
qal
1
nroim
2
1
eflomal
WLC
aaz_C01
hbo:0014
qal
1
nroim
2
1
gloss
WLC
aaz_C01
hbo:0028
1
abida
1
1
eflomal
WLC
aaz_C01
hbo:0028
1
abida
1
1
gloss
WLC
aaz_C01
hbo:0040
1
uisf
8
0.3636
gloss
WLC
aaz_C01
hbo:0040
1
usif
6
0.2727
gloss
WLC
aaz_C01
hbo:0040
1
abimerek
6
0.2727
gloss
WLC
aaz_C01
hbo:0040
1
uisf
5
0.2273
eflomal
WLC
aaz_C01
hbo:0040
1
usif abimerek
5
0.2273
eflomal
WLC
aaz_C01
hbo:0040
1
abimerek
4
0.1818
eflomal
WLC
aaz_C01
hbo:0040
1
usif
3
0.1364
eflomal
WLC
aaz_C01
hbo:0040
1
uisf ee
2
0.0909
eflomal
WLC
aaz_C01
hbo:0040
1
abimerek usif
1
0.0455
eflomal
WLC
aaz_C01
hbo:0040
1
antenin
1
0.0455
eflomal
WLC
aaz_C01
hbo:0040
1
nakain
1
0.0455
eflomal
WLC
aaz_C01
hbo:0040
1
usiꞌ
1
0.0455
gloss
WLC
aaz_C01
hbo:0040
1
usi
1
0.0455
gloss
WLC
aaz_C01
hbo:0046
1
mukrao mbaras
1
1
eflomal
WLC
aaz_C01
hbo:0046
1
mukrao mbaras
1
1
gloss
WLC
aaz_C01
hbo:0056
hithpael
1
nsuus
1
1
eflomal
WLC
aaz_C01
hbo:0056
hithpael
1
nsuus
1
1
gloss
WLC
aaz_C01
hbo:0057
2
ꞌnanaꞌreen
1
1
eflomal
WLC
aaz_C01
hbo:0057
2
ꞌnanaꞌreen
1
1
gloss
WLC
aaz_C01
hbo:0060
1
nbeꞌen nteinꞌ fai
1
0.5
eflomal
WLC
aaz_C01
hbo:0060
1
nbeꞌen amates
1
0.5
eflomal
WLC
aaz_C01
hbo:0060
1
nbeꞌen
1
0.5
gloss
WLC
aaz_C01
hbo:0060
1
nbeꞌen amates
1
0.5
gloss
WLC
aaz_C01
hbo:0067
1
abel
1
1
eflomal
WLC
aaz_C01
hbo:0067
1
abel
1
1
gloss
WLC
aaz_C01
hbo:0068
1
faut
7
0.5833
gloss
WLC
aaz_C01
hbo:0068
1
fatu
5
0.4167
gloss
WLC
aaz_C01
hbo:0068
1
fatu
3
0.2308
eflomal
WLC
aaz_C01
hbo:0068
1
faut
2
0.1538
eflomal
WLC
aaz_C01
hbo:0068
1
faut goes
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
faut akaꞌnunuꞌ
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
fatu njair
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
faut kouꞌ goes
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
mtitar fatu
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
faut tobef
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
njair
1
0.0769
eflomal
WLC
aaz_C01
hbo:0068
1
kuasn
1
0.0769
eflomal
WLC
aaz_C01
hbo:0085
1
abraham
95
0.9223
gloss
WLC
aaz_C01
hbo:0085
1
naiꞌ abraham
69
0.69
eflomal
WLC
aaz_C01
hbo:0085
1
abraham
11
0.11
eflomal
WLC
aaz_C01
hbo:0085
1
naiꞌ
6
0.0583
gloss
WLC
aaz_C01
hbo:0085
1
naiꞌ
3
0.03
eflomal
WLC
aaz_C01
hbo:0085
1
isak
3
0.03
eflomal
WLC
aaz_C01
hbo:0085
1
naꞌi naiꞌ abraham
3
0.03
eflomal
WLC
aaz_C01
hbo:0085
1
nbaiseun
1
0.01
eflomal
WLC
aaz_C01
End of preview. Expand in Data Studio

senses_attested — attested target renderings per lexeme sense

The empirical evidence layer produced for shoresh (bcv-query data-contract): for a lexeme in a disambiguated (binyan, sense), which target-language words attest it, with counts. It is the supply that fills shoresh's senses_i18n/_gaps demand and cross-checks the llm_strongs_glosses predictions — it does not replace shoresh's curated senses_i18n/<iso>.tsv; consumed as an HF Parquet dataset.

Schema (per row)

column meaning
lexeme MACULA lexeme (the anchor), e.g. hbo:0006
stem MACULA binyan (qal/piel/hiphil/…); empty for non-verbs
sense sense number (ordinal) — see licensing
surface attested target rendering (lowercased)
count times this (lexeme, stem, sense) → surface was aligned
share count / Σ count for that (lexeme, stem, sense) within one base_text
method alignment method (eflomal)
source_corpus the original Hebrew corpus (e.g. WLC)
base_text the target edition attested (e.g. ind_C01) — the per-row provenance dimension

Key: (lexeme, stem, sense) — MACULA lexeme (anchor; BHSA lex dropped) + MACULA binyan + sense number, read inline from the enriched lexeme-spine.db. OT/Hebrew only (senses are Hebrew; Greek tokens carry none).

Multi-version: base_text is per-row, so several translations of a language are pooled into one iso=<lang> partition — a union of per-edition runs, each row tagged by edition; share stays per-edition. Cross-edition agreement (how many base_texts attest a given (lexeme,stem,sense)→ surface) is the confidence signal, derivable directly from the rows. (Swedish iso=swe pools swe_fol Folkbibeln + swe_svk Kärnbibeln.)

Removal / takedown policy

Each row is a per-edition attestation carrying its base_text, so a rights-holder can request removal and it is a clean row-drop + republish (the dataset is content-addressed via each partition's content_sha256). Because most (lexeme,stem,sense)→surface facts are attested by more than one edition, dropping one edition typically leaves the linguistic fact intact via the others — properly attributed. Rows are never re-emitted with provenance stripped: a removed attestation is removed, not anonymized.

Removals are driven by a committed, auditable config: data/senses_exclude.json (read automatically on every build). A row is dropped if it matches any rule; a rule matches when all its stated fields equal the row's — fields lexeme, stem, sense, surface, base_text, omit to wildcard:

{"exclude": [
  {"base_text": "swe_fol"},                       // drop a whole edition
  {"base_text": "swe_fol", "surface": "herren"}   // drop one surface within an edition
]}

After exclusion, survivor shares renormalise (per edition), so a removed row leaves no residue; the manifest records excluded: {rules, rows_dropped} for the audit trail. To action a takedown: add a rule, re-run senses_attested for the affected language, republish.

Licensing — CC-BY-4.0, deliberately label-free

The key is MACULA-derived (lexeme + binyan), so this dataset is CC-BY-4.0 — attribute Clear-Bible MACULA. We carry the sense number only and no English sense label: shoresh's sense labels are UBS-MARBLE "used with permission" (not redistributable), so the payload is pure attestation (lexeme, stem, sense#, surface, count) — CC-BY clean. Regenerate: python -m lexeme_aligner.senses_attested --iso <iso> --method eflomal. Same git-ignored-Parquet + committed-manifest.json layout as lexeme-alignments.

Downloads last month
63