| --- |
| dataset_info: |
| features: |
| - name: id |
| dtype: string |
| - name: entry_id |
| dtype: int64 |
| - name: entry_heading |
| dtype: string |
| - name: context |
| dtype: string |
| - name: sense_id |
| dtype: int64 |
| - name: candidates |
| list: |
| - name: sense_id |
| dtype: int64 |
| - name: gloss |
| dtype: string |
| splits: |
| - name: train |
| num_bytes: 15904118 |
| num_examples: 33231 |
| - name: val |
| num_bytes: 3130154 |
| num_examples: 6154 |
| - name: test |
| num_bytes: 7058582 |
| num_examples: 14979 |
| download_size: 5792286 |
| dataset_size: 26092854 |
| configs: |
| - config_name: default |
| data_files: |
| - split: train |
| path: data/train-* |
| - split: val |
| path: data/val-* |
| - split: test |
| path: data/test-* |
| license: cc-by-4.0 |
| pretty_name: Latvian WSD |
| --- |
| |
| # Latvian WSD |
|
|
| A manually annotated Latvian **word sense disambiguation (WSD)** dataset based on example sentences from the Latvian WordNet. |
|
|
| Each sentence is linked to a specific word sense. Lemmas with only a single sense are excluded. The dataset contains 1,821 lemmas and 5,459 unique senses. |
|
|
| ## Data Format |
|
|
| Each example contains: |
|
|
| * `id`: instance identifier |
| * `entry_id`: entry identifier |
| * `entry_heading`: entry heading (lemma) |
| * `context`: sentence containing the target word |
| * `sense_id`: correct sense identifier |
| * `candidates`: list of candidate senses, each with: |
| * `sense_id`: candidate sense identifier |
| * `gloss`: sense definition |
|
|
| ## Splits |
|
|
| The dataset is split by entry to avoid lexical overlap: |
|
|
| | Split | Lemmas | Instances | |
| | ---------- | -------- | ---------- | |
| | Train | 1121 | 33,231 | |
| | Validation | 200 | 6,154 | |
| | Test | 500 | 14,979 | |
| | **Total** | **1821** | **54,364** | |
|
|
| ## Citation |
|
|
| ```bibtex |
| @inproceedings{paikens-etal-2022-towards, |
| title = "Towards {L}atvian {W}ord{N}et", |
| author = "Paikens, Peteris and |
| Grasmanis, Mikus and |
| Klints, Agute and |
| Lokmane, Ilze and |
| Pretkalni{\c{n}}a, Lauma and |
| Rituma, Laura and |
| St{\={a}}de, Madara and |
| Strankale, Laine", |
| booktitle = "Proceedings of the Thirteenth Language Resources and Evaluation Conference", |
| month = jun, |
| year = "2022", |
| address = "Marseille, France", |
| publisher = "European Language Resources Association", |
| url = "https://aclanthology.org/2022.lrec-1.300/", |
| pages = "2808--2815" |
| } |
| ``` |
|
|
| ```bibtex |
| @inproceedings{znotins-2026-pretraining, |
| title = "Pretraining and Benchmarking Modern Encoders for {L}atvian", |
| author = "Znotins, Arturs", |
| booktitle = "Proceedings of the Second Workshop on Language Models for Low-Resource Languages ({L}o{R}es{LM} 2026)", |
| month = mar, |
| year = "2026", |
| address = "Rabat, Morocco", |
| publisher = "Association for Computational Linguistics", |
| url = "https://aclanthology.org/2026.loreslm-1.40/", |
| doi = "10.18653/v1/2026.loreslm-1.40", |
| pages = "461--470", |
| ISBN = "979-8-89176-377-7" |
| } |
| ``` |
