Please note: The algorithm descriptions in English have been automatically translated. Errors may have been introduced in this process. For the original descriptions, go to the Dutch version of the Algorithm Register.

Text analysis

Based on language technology, personal and company names are read and filtered out of text files such as emails and individual documents.

Last change on 1st of December 2025, at 9:54 (CET) | Publication Standard 1.0
Publication category
Other algorithms
Impact assessment
Field not filled in.
Status
In use

General information

Theme

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Begin date

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Contact information

algoritmes@leidse-regio.nl

Responsible use

Goal and impact

Support in the review process where legal protections apply to information disclosed. Protection from the AVG (persons) and Woo laws (especially company confidential), where grounds for exception are named.

Considerations

Manual review is intensive and error-prone. A suggestion list from the entity extraction algorithm captures all conceivable instances of individuals in the text.

Human intervention

Within the software, a list is built and offered to the user to select in the automatic varnishing process. The choice to adopt an advised term as a personal name and not to disclose it is up to the user.

Risk management

There is no risk of automated decision-making and the algorithm has no impact on fundamental rights because the algorithm does not make decisions with legal consequences. It only makes a proposal for anonymising personal data. The municipal employee always does the final check whether a document is correctly anonymised.

Legal basis

Legislation around public access to government data (Woo)

Links to legal bases

Open Government Act: https://wetten.overheid.nl/BWBR0045754/2023-04-01#Hoofdstuk5

Link to Processing Index

https://leiden.registervanverwerkingen.nl/details/dcd57383-36a6-4716-9038-7e40243f6b45

Operations

Data

This refers to documents and messaging information within the municipality. Including email, files, Whatsapp messages and other media where administrative decision-making can be found.

Links to data sources

General Office applications: Dit betreft standaard Office formaten inclusief email en social media formaten.

Technical design

Texts are recognised on the basis of Named Entity Recognition (NER) and a process within Insights extracts the names for further processing towards the management interface and the automatic lacquer rules.

External provider

ZyLAB eDiscovery & Compliance Services B.V.

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