SIMARA (SIMARA: a database for key-value information extraction from full-page handwritten documents)

Introduced by Tarride et al. in SIMARA: a database for key-value information extraction from full pages

Description

We propose a new database for information extraction from historical handwritten documents. The corpus includes 5,393 finding aids from six different series, dating from the 18th-20th centuries. Finding aids are handwritten documents that contain metadata describing older archives. They are stored in the National Archives of France and are used by archivists to identify and find archival documents.

Each document is annotated at page-level, and contains seven fields to retrieve. The localization of each field is not available in such a way that this dataset encourages research on segmentation-free systems for information extraction.

The dataset is available at https://zenodo.org/record/7868059

Details for each series and entity type

Series Train Validation Test Total (%)
E series 322 64 79 8.6
L series 38 8 4 0.9
M series 128 21 27 3.3
X1a series 2209 491 469 58.8
Y series 940 205 196 24.9
Douët s'Arcq series 141 22 29 3.5
Total 3778 811 804 100
Entities Train Validation Test Total (%)
date 8406 1814 1799 10.4
title 35531 7495 8173 44.5
serie 3168 664 676 3.9
analysis 25988 5130 5602 31.9
volume_number 3913 808 813 4.8
article_number 3181 665 678 3.9
arrangement 644 122 153 0.8
Total 80831 16698 17894 100

Data encoding

Transcriptions with entities are encoded in the labels.json JSON file. Special tokens are used to represent named entities. Please not that there are only opening NER tokens: each entity spans all words until the next entity starts.

Entities Special token Symbol unicode
date \u24d3
title \u24d8
serie \u24e2
analysis \u24d2
volume_number \u24df
article_number \u24d0
arrangement \u24e5

Cite us!

The dataset is presented in details in the following article:

@article{simara2023,
    author = {Solène Tarride and Mélodie Boillet and Jean-François Moufflet and Christopher Kermorvant},
    title = {SIMARA: a database for key-value information extraction from full-page handwritten documents},
    year = {2023},
    journal={Proceedings of the 17th International Conference on Document Analysis and Recognition},
}

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