olaverse/diacnet-1.1-gloss
DiacNet 1.1 Ambiguity Lexicon & Gloss Tables Per-language tables of diacritic-ambiguous words — words whose diacritic-stripped form maps to two or more distinct diacritized variants — extracted from the diacnet-1.1-corpus and annotated with variant type and English glosses. Built to power the gloss-conditioning feature of diacnet-1.1: at training time, ambiguous words in the input can be annotated with their intended English meaning (e.g. [g: ogun=war]), teaching the model to… See the full description on the dataset page: https://huggingface.co/datasets/olaverse/diacnet-1.1-gloss.
DiacNet 1.1 Ambiguity Lexicon & Gloss Tables
Per-language tables of diacritic-ambiguous words — words whose diacritic-stripped form maps to two or more distinct diacritized variants — extracted from the diacnet-1.1-corpus and annotated with variant type and English glosses.
Built to power the gloss-conditioning feature of diacnet-1.1: at training time, ambiguous words in the input can be annotated with their intended English meaning (e.g. [g: ogun=war]), teaching the model to use user-supplied sense hints when restoring diacritics. Only variants typed sense participate in gloss injection; the other types feed marking-consistency augmentation instead.
Files & loading
One CSV per language (gloss_curate_{lang}.csv), each exposed as a config:
from datasets import load_dataset
yor = load_dataset("olaverse/diacnet-1.1-gloss", "yor", split="train")or as plain CSVs:
from huggingface_hub import hf_hub_download
import pandas as pd
df = pd.read_csv(hf_hub_download("olaverse/diacnet-1.1-gloss",
"gloss_curate_yor.csv", repo_type="dataset"))Schema
type semantics
- `sense` — genuine lexical/grammatical ambiguity: the variants are different words or word-forms whose distinction is recoverable only from context or an external hint (e.g. Yorùbá
ogún"twenty/inheritance" vsògùn"medicine/charm"; Spanishtérmino"term" vsterminó"he/she finished"; Vietnamesesách"book" vssạch"clean"). These rows drive gloss injection. - `spelling_variant` — same lexeme, different marking completeness or legal orthographic alternatives (e.g. Yorùbá
ninuvsnínú, both "inside"; Portugueseeconômica/económica, Brazilian vs European norm; Italianperché/perchè). Used for marking-consistency training, not glossing. - `proper_noun` — names/places with transliteration variance (Nàìjíríà, Söke, Elysée, Antônio/António).
- `skip` — excluded rows: encoding noise (e.g. Vietnamese forms using
ð(eth) instead ofđ) or unresolvable low-frequency items.
How it was built
- Tokenized the full
diacnet-1.1-corpustrain split per language; grouped words by diacritic-stripped form. - Kept groups with ≥2 variants each clearing an absolute frequency floor (≥20) and a minimum share of the group (≥2%) — filtering out OCR/typo tails masquerading as variants.
- Kept only groups with ≥2 distinctly marked variants (a bare form plus one marked form is marking-completeness noise, not ambiguity).
- Content words prioritized (stripped length > 3); note the limitation on monosyllables below.
typeandgloss_endrafted by an LLM (Claude) using per-language strategies: rule-based classification for regular grammatical patterns (Polish case alternation, French participle/present, Spanish stress-accent grammar) plus hand-curated entries for lexical polysemy; Vietnamese glossed fully by hand (399/401 groups); Yorùbá curated conservatively against dictionary-attested tonal minimal pairs.
Per-language statistics
The cross-language pattern is itself informative: Vietnamese ambiguity is near-total (tonal monosyllabic language — stripping tones collapses the lexicon), Spanish/Polish/French ambiguity is mostly grammatical (stress-accent, case, tense distinctions), Italian has essentially none (accent pairs are standard-vs-misspelling), and Yorùbá/Igbo/Hausa corpus variance is dominated by marking completeness rather than polysemy — with a small, high-value core of true tonal minimal pairs in Yorùbá.
Known limitations
- Annotations are LLM-drafted, not native-speaker-verified. Rows whose gloss contains
[REVIEW](16 total, concentrated in yor/ibo/hau) are explicitly uncertain. A native-speaker pass over Yorùbá and Hausasenserows is recommended before treating those glosses as ground truth. Report corrections via the community tab. - Yorùbá monosyllables are under-represented. The extraction deprioritized stripped forms ≤3 characters as probable function words — but much of Yorùbá's real tonal polysemy lives in monosyllabic verbs (
sọ/só,wá/wà,gbà/gbá,bá/bà,lọ/lo,rí/rì,fẹ́/fẹ̀). A supplementary monosyllable table is planned. - Frequencies reflect the diacnet-1.1-corpus (FineWeb-2 + Wikipedia after density filtering), not general language use; register skews toward web/encyclopedic text.
- Vietnamese glosses give the dominant meaning(s) with a disambiguating example compound; many syllables have additional senses not listed.
Provenance & license
Derived from diacnet-1.1-corpus (FineWeb-2, ODC-By 1.0; Wikipedia, CC BY-SA 4.0). Released under ODC-By 1.0. Attribute upstream sources per their terms.
Citation
@dataset{diacnet_1_1_gloss,
author = {olaverse},
title = {DiacNet 1.1 Ambiguity Lexicon \& Gloss Tables},
year = {2026},
publisher = {Hugging Face},
url = {https://huggingface.co/datasets/olaverse/diacnet-1.1-gloss}
}