aleph data search
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Pinned repositories
Repositories
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aleph
Search and browse documents and data; find the people and companies you look for.
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followthemoney-predict
Experiments with FtM record linkage
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ingest-file
Ingestors extract useful information in a structured standard format.
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servicelayer
Common interface definitions for aleph toolkit services and applications
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translate-service
Demo: document processing service for automated translation
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docs
GitHub mirror of the GitBook documentation
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followthemoney
Data model and processing tools for investigative entity data
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react-ftm
React UI component library for aleph/followthemoney
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memorious
Distributed crawling framework for documents and structured data.
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opensanctions
An open database of persons of interest and politically exposed persons
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aleph-helm-charts
Helm charts for Aleph
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alephclient
API client for Aleph, supports bulk entity and document upload.
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datadesktop
Desktop graph visualization application
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datacommons
A fleet of Memorious scrapers for crawling various open data sources
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convert-document
A docker container for LibreOffice and unoconv, used to generate PDF files from office-type documents.
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msglite
Forked from TeamMsgExtractor/msg-extractorExtracts emails and attachments saved in Microsoft Outlook's .msg files
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followthemoney-store
Fragment storage layer for FollowTheMoney entities (formerly "balkhash")
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offshoreleaks
Converter for ICIJ Offshore Leaks data into FollowTheMoney format
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languagecodes
A Python helper library to convert between ISO 639 two- and three-letter codes.
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synonames
Trying to generate name synonyms from wikidata
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pdflib
Binary Python bindings for poppler utils for content extraction
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ideas
Long-term development ideas for the Aleph toolkit
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followthemoney-cellebrite
Generate FollowTheMoney entities from Cellebrite XML reports
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followthemoney-ocds
Import data formatted as OpenContracting Data Standard (OCDS) objects into FollowTheMoney
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example-personadeinteres
Example how to load mixed document/entity graphs to Aleph
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fingerprints
Make it easier to compare and cross-reference the names of companies and people by applying strong normalisation.