Dataset Card for panlex-definitions

This is a dataset of word definitions in several hudnred languages, extracted from https://panlex.org.

Dataset Details

Dataset Description

This dataset has been extracted from https://panlex.org (the 20250201 database dump) and rearranged on the per-language basis (by the language of the definition).

Each language subset consists of definitions (short phrases). Each definition is associated with some meanings (if there is more than one meaning, they are in separate rows). Each meanning is associated with one or more words (and occasionally, there are no words for a meaning, for a reason unknown to me). The database currently contains only one word per meaning, chosen arbitrary. To match a meaning with multiple words, please join the dataset with cointegrated/panlex-meanings.

Thus, by joining per-language datasets by meaning ids, one can obtain a bilingual dictionary for the chosen language pair.

• Curated by: David Dale (@cointegrated), based on a snapshot of the Panlex database (https://panlex.org/snapshot).
• Language(s) (NLP): The Panlex database mentions 7558 languages, but only 6241 of them have at least one entry (where entry is a combination of expression and meaning), and only 1012 have at least 1000 entries. These 1012 languages are tagged in the current dataset.
• License: CC0 1.0 Universal License, as explained in https://panlex.org/license.

Dataset Sources [optional]

• Original website: https://panlex.org/
• Paper: Kamholz, David, Jonathan Pool, and Susan M. Colowick. 2014. PanLex: Building a Resource for Panlingual Lexical Translation. Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014).

Uses

The intended use of the dataset is to extract monolingual or bilingual dictionaries for the purposes of language learning by machines or humans.

The code below illustrates how the dataset could be used to extract all French definitions of Finnish words found on Panlex.

from datasets import load_dataset
ds_fin_word = load_dataset('cointegrated/panlex-meanings', name='fin', split='train')
ds_fra_def = load_dataset('cointegrated/panlex-definitions', name='fra', split='train')
df_fin_word = ds_fin_word.to_pandas()
df_fra_def = ds_fra_def.to_pandas()

df_matched = df_fin_word.merge(df_fra_def, on='meaning', suffixes=['_wrd', '_def']).drop_duplicates(subset=['txt_wrd', 'txt_def'])
print(df_matched.shape)
# (11512, 13)

print(df_matched.sample(5)[['txt_wrd', 'meaning', 'txt_def']])
#                txt_wrd   meaning                                    txt_def
# 101   kalsiumpitoisuus  30766618                          teneur en calcium
# 7003              keho  28131094  Partie matérielle de tout être animé. (2)
# 8180      mikä tahansa  27960302                    quel que soit celui qui
# 4606            Safari   1689224                          Safari (logiciel)
# 9833        suositella  28251812                                    à trier

Dataset Structure

The dataset is split by languages of the definition, 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 definition
• meaning (int): id of the meaning, joinable with cointegrated/panlex-meanings
• langvar (int): id of the language variety of the definition
• txt (str): text of the definition
• langvar_uid (str): more human-readable id of the definition 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/.
• example (str, optional): example of a word corresponding to the meaning of the definition (preferably, but not always, in the language of the definition)
• example_langvar (int, optional): id of the language variety of the example
• example_langvar_uid (str, optional): human-readable id of the language variety of the example

Dataset Creation

This dataset has been extracted from https://panlex.org (the 20250201 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 definition table.
3. Joining the selected set with the denotation table, to match an example of expression id with the given meaning, and then with the expr table, to get the text and language of the expression.

Bias, Risks, and Limitations

As with any multilingual dataset, Panlex data may exhbit the problem of under- and mis-representation of some languages.

Citation

Kamholz, David, Jonathan Pool, and Susan M. Colowick. 2014. PanLex: Building a Resource for Panlingual Lexical Translation. Proceedings of the 9th International Conference on Language Resources and Evaluation (LREC 2014).

BibTeX:

@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 and database design.