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Published February 11, 2025 | Version v2

Entities recognised in the resolutions of the States General of the Dutch Republic (1576-1796)

Description

These files contain curated sets of recognised entities in the resolutions of the States General of the Dutch Republic between 1576 and 1796. The following entity types are present:

Abbreviation Name Description
COM Commissies Internal committees of the States General
DAT Datums Dates referencing other resolutions
HOE Hoedanigheden Roles and functions of persons
LOC Locaties Geographical locations
ORG Organisaties Organisations, Institutions, Polities
PER Persoonsnamen Personal names

 

Associated with every entity type except DAT are two files: one containing entities and entity metadata, the other containing the annotations on the text of the resolutions that point to forementioned entities.

The entity metadata files contain the following fields:

Field Description
id Identifier linking entities to annotations
name Canonical name
comment Additional information
category Entity type
labels Entity categories
links Links to external datasets
geo_data Geographical information (LOC only)

 

The annotation files contain the following fields:

Field Description
reference Identifies the annotated text fragment
entity Entity identifier (not for DAT)
date Referenced date (DAT only)
provenance Provenance of the entity assignment

 

Update 2025-02-11: The raw NER output is now also included. There is one file per entity type, with 8 fields:

Field Description
layer Entity type
inv Inventory Number (book identifier)
resolution_id resolution identifier (identifies the resolution in the corresponding book)
paragraph_id paragraph identifier (corresponds to a paragraph in the resolution)
tag_text the text string that was tagged as an entity
offset the character offset of the text string in the paragraph
end the character end offset of the text string
tag_length the character length of the text string

Files

COM-annotations.json

Files (8.6 GB)

Name Size
md5:58da7918385f5cd8fd189b236d6a6ede
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md5:1cfc63beeb33e3fb10296d509f6c3a31
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Additional details

Related works

Is derived from
Dataset: 10.5281/zenodo.14224102 (DOI)

Funding

Dutch Research Council
Investment Grant NWO Large 175.2017.024

Software

Repository URL
https://github.com/huygensING/republic-project/
Programming language
Python , Awk