--- 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. The rearrangement consisted of the following steps: 1. Grouping together the language varieties from the `langvar` table with the same `lang_code`. 2. For each language, selecting the corresponding subset from the `expr` table. 3. Joining the selected set with the `denotation` table, to get the `meaning` id. This increases the number of rows (for some languages, x5), because multiple meannings may be attached to the same expression. ## Bias, Risks, and Limitations As with any multilingual dataset, Panlex data may exhbit the problem of under- and mis-representation of some languages. The dataset consists primarily of the standard written forms ("lemmas") of the expressions, so it may not well represent their usage within a language. ## Citation 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). **BibTeX:** ```bib @inproceedings{kamholz-etal-2014-panlex, title = "{P}an{L}ex: Building a Resource for Panlingual Lexical Translation", author = "Kamholz, David and Pool, Jonathan and Colowick, Susan", editor = "Calzolari, Nicoletta and Choukri, Khalid and Declerck, Thierry and Loftsson, Hrafn and Maegaard, Bente and Mariani, Joseph and Moreno, Asuncion and Odijk, Jan and Piperidis, Stelios", booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)", month = may, year = "2014", address = "Reykjavik, Iceland", publisher = "European Language Resources Association (ELRA)", url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/1029_Paper.pdf", pages = "3145--3150", abstract = "PanLex, a project of The Long Now Foundation, aims to enable the translation of lexemes among all human languages in the world. By focusing on lexemic translations, rather than grammatical or corpus data, it achieves broader lexical and language coverage than related projects. The PanLex database currently documents 20 million lexemes in about 9,000 language varieties, with 1.1 billion pairwise translations. The project primarily engages in content procurement, while encouraging outside use of its data for research and development. Its data acquisition strategy emphasizes broad, high-quality lexical and language coverage. The project plans to add data derived from 4,000 new sources to the database by the end of 2016. The dataset is publicly accessible via an HTTP API and monthly snapshots in CSV, JSON, and XML formats. Several online applications have been developed that query PanLex data. More broadly, the project aims to make a contribution to the preservation of global linguistic diversity.", } ``` ## Glossary To understand the terms like "language", "language variety", "expression" and "meaning" more precisely, please read the Panlex documentation on their [data model]( https://dev.panlex.org/data-model/) and [database design](https://dev.panlex.org/database-design/).