---
dataset_info:
- config_name: cappelli
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: metadata
    struct:
    - name: abbr_class
      dtype: string
    - name: bbox
      list: int64
    - name: category
      dtype: string
    - name: normalized
      dtype: string
    - name: page_id
      dtype: int64
    - name: period
      dtype: string
    - name: positions
      list: string
    - name: source
      dtype: string
  splits:
  - name: train
    num_bytes: 4582754
    num_examples: 14329
  download_size: 819527
  dataset_size: 4582754
- config_name: clean
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: metadata
    struct:
    - name: english_def
      dtype: string
    - name: latin_term
      dtype: string
    - name: source
      dtype: string
  splits:
  - name: train
    num_bytes: 730585
    num_examples: 4313
  download_size: 361684
  dataset_size: 730585
- config_name: kriston
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: metadata
    struct:
    - name: english_def
      dtype: string
    - name: latin_term
      dtype: string
    - name: source
      dtype: string
  splits:
  - name: train
    num_bytes: 1192774
    num_examples: 7834
  download_size: 530447
  dataset_size: 1192774
- config_name: words
  features:
  - name: id
    dtype: string
  - name: text
    dtype: string
  - name: metadata
    struct:
    - name: english_def
      dtype: string
    - name: grammar
      dtype: string
    - name: latin_term
      dtype: string
    - name: source
      dtype: string
  splits:
  - name: train
    num_bytes: 7673814
    num_examples: 30352
  download_size: 3056664
  dataset_size: 7673814
configs:
- config_name: cappelli
  data_files:
  - split: train
    path: cappelli/train-*
- config_name: clean
  data_files:
  - split: train
    path: clean/train-*
- config_name: kriston
  data_files:
  - split: train
    path: kriston/train-*
- config_name: words
  data_files:
  - split: train
    path: words/train-*
---

Interpres RAG Collection (IRC) contains the Medieval Latin dictionaries like [Medieval Latin Word Vocabulary](https://kriston.net/tools/latin/medieval.shtml), [William Whitaker's Words](https://kriston.net/tools/latin/words.shtml), [Lexicon Abbreviaturarum](https://www.adfontes.uzh.ch/en/ressourcen/abkuerzungen/cappelli-online), and [the English to Latin Dictionary](http://dadako.narod.ru/GoldenDict/eng-lat_Latin_1_0.zip). Together with parallel copara include [grosenthal/latin_english_parallel](https://huggingface.co/datasets/grosenthal/latin_english_parallel) and [magistermilitum/tridis_translate_la_en](https://huggingface.co/datasets/magistermilitum/tridis_translate_la_en) the vector database for RAG system of Interpres is formed.