--- license: cc0-1.0 task_categories: - translation size_categories: - 10M - **Original website:** https://panlex.org/ - **Paper:** Kamholz, David, Jonathan Pool, and Susan M. Colowick. 2014. [PanLex: Building a Resource for Panlingual Lexical Translation](http://www.lrec-conf.org/proceedings/lrec2014/pdf/1029_Paper.pdf). Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014). ## Uses The intended use of the dataset is to extract bilingual dictionaries for the purposes of language learning by machines or humans. The code below illustrates how the dataset could be used to extract a bilingual Avar-English dictionary. ```Python from datasets import load_dataset ds_ava = load_dataset('cointegrated/panlex-meanings', name='ava', split='train') ds_eng = load_dataset('cointegrated/panlex-meanings', name='eng', split='train') df_ava = ds_ava.to_pandas() df_eng = ds_eng.to_pandas() df_ava_eng = df_ava.merge(df_eng, on='meaning', suffixes=['_ava', '_eng']).drop_duplicates(subset=['txt_ava', 'txt_eng']) print(df_ava_eng.shape) # (10565, 11) print(df_ava_eng.sample(5)[['txt_ava', 'txt_eng', 'langvar_uid_ava']]) # txt_ava txt_eng langvar_uid_ava # 7921 калим rug ava-002 # 3279 хІераб old ava-001 # 41 бакьулълъи middle ava-000 # 9542 шумаш nose ava-006 # 15030 гӏащтӏи axe ava-000 ``` Apart from these direct translations, one could also try extracting multi-hop translations (e.g. enrich the direct Avar-English word pairs with the word pairs that share a common Russian translation). However, given that many words have multiple meaning, this approach usually generates some false translations, so it should be used with caution. ## Dataset Structure The dataset is split by languages, denoted by their ISO 639 codes. Each language might contain multiple varieties; they are annotated within each per-language split. To determine a code for your language, please consult the https://panlex.org webside. For additional information about a language, you may also want to consult https://glottolog.org/. Each split contains the following fields: - `id` (int): id of the expression - `langvar` (int): id of the language variaety - `txt` (str): the full text of the expression - `txt_degr` (str): degraded (i.e. simplified to facilitate lookup) text - `meaning` (int): id of the meaning. This is the column to join for obtaining synonyms (within a language) or translations (across languages) - `langvar_uid` (str): more human-readable id of the language (e.g. `eng-000` stands for generic English, `eng-001` for simple English, `eng-004` for American English). These ids could be looked up in the language dropdown at https://vocab.panlex.org/. ## Dataset Creation This dataset has been extracted from https://panlex.org (the `20240301` database dump) and automatically rearranged on the per-language basis. ## Bias, Risks, and Limitations [More Information Needed] ### Recommendations Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations. ## Citation [optional] **BibTeX:** [More Information Needed] **APA:** [More Information Needed] ## Glossary [optional] [More Information Needed] ## More Information [optional] [More Information Needed] ## Dataset Card Authors [optional] [More Information Needed] ## Dataset Card Contact [More Information Needed]