---
license: odc-by
language:
- yo
- ig
- ha
- vi
- pl
- tr
- pt
- es
- fr
- it
multilinguality: multilingual
pretty_name: DiacNet 1.1 Ambiguity Lexicon & Gloss Tables
size_categories:
- 1K<n<10K
tags:
- diacritics
- diacritization
- word-sense-disambiguation
- lexicon
- glossary
- yoruba
- igbo
- hausa
- vietnamese
configs:
- config_name: yor
  data_files: gloss_curate_yor.csv
- config_name: ibo
  data_files: gloss_curate_ibo.csv
- config_name: hau
  data_files: gloss_curate_hau.csv
- config_name: vie
  data_files: gloss_curate_vie.csv
- config_name: pol
  data_files: gloss_curate_pol.csv
- config_name: tur
  data_files: gloss_curate_tur.csv
- config_name: por
  data_files: gloss_curate_por.csv
- config_name: spa
  data_files: gloss_curate_spa.csv
- config_name: fra
  data_files: gloss_curate_fra.csv
- config_name: ita
  data_files: gloss_curate_ita.csv
---

# 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](https://huggingface.co/datasets/olaverse/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:

```python
from datasets import load_dataset
yor = load_dataset("olaverse/diacnet-1.1-gloss", "yor", split="train")
```

or as plain CSVs:

```python
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

| Column | Type | Description |
|---|---|---|
| `stripped` | string | Diacritic-stripped surface form shared by all variants in the group |
| `variant` | string | A diacritized form found in the corpus (NFC) |
| `freq` | int | Corpus frequency of this variant |
| `total_freq` | int | Combined frequency of all retained variants in the group |
| `type` | string | `sense` \| `spelling_variant` \| `proper_noun` \| `skip` (see below) |
| `gloss_en` | string | English gloss — filled only for `sense` rows; may carry a `[REVIEW]` flag |

### `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" vs `ògùn` "medicine/charm"; Spanish `término` "term" vs `terminó` "he/she finished"; Vietnamese `sách` "book" vs `sạch` "clean"). These rows drive gloss injection.
- **`spelling_variant`** — same lexeme, different marking completeness or legal orthographic alternatives (e.g. Yorùbá `ninu` vs `nínú`, both "inside"; Portuguese `econômica`/`económica`, Brazilian vs European norm; Italian `perché`/`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 of `đ`) or unresolvable low-frequency items.

## How it was built

1. Tokenized the full `diacnet-1.1-corpus` train split per language; grouped words by diacritic-stripped form.
2. 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.
3. Kept only groups with ≥2 *distinctly marked* variants (a bare form plus one marked form is marking-completeness noise, not ambiguity).
4. Content words prioritized (stripped length > 3); note the limitation on monosyllables below.
5. `type` and `gloss_en` drafted 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

| lang | groups | rows | `sense` rows | sense groups | spelling_variant | proper_noun | skip | ⚠ review-flagged |
|---|---:|---:|---:|---:|---:|---:|---:|---:|
| yor | 1,126 | 2,487 | 44 | 19 | 2,440 | 3 | 0 | 11 |
| ibo | 152 | 315 | 8 | 3 | 307 | 0 | 0 | 2 |
| hau | 14 | 28 | 6 | 3 | 20 | 2 | 0 | 2 |
| vie | 401 | 1,191 | 1,185 | 399 | 0 | 0 | 6 | 0 |
| pol | 244 | 488 | 470 | 235 | 18 | 0 | 0 | 0 |
| tur | 79 | 159 | 87 | 43 | 72 | 0 | 0 | 1 |
| por | 44 | 88 | 12 | 6 | 70 | 6 | 0 | 0 |
| spa | 20 | 40 | 38 | 19 | 2 | 0 | 0 | 0 |
| fra | 199 | 401 | 387 | 192 | 12 | 2 | 0 | 0 |
| ita | 18 | 36 | 0 | 0 | 30 | 6 | 0 | 0 |

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 Hausa `sense` rows 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](https://huggingface.co/datasets/olaverse/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}
}
```