Dataset
French-Patents-2020-2026-Raw
Raw French patent publications from 2020 through 2026, pulled from original A1 XML records by an independent API/FTP extraction and delivered one-document-per-row in streaming-ready parquet.
Data preview
Dataset card
French-Patents-2020-2026-Raw is a Hugging Face dataset published by INPI-France containing French patent publications (kind A1) extracted from original XML source files, with one document per row. It is distributed in Parquet format and is hosted under an unstated license.
What this dataset contains
The dataset aggregates published French patent documents (A1 publications) parsed from official INPI XML feeds accessed via API or FTP. Each record corresponds to a single patent document held as full text rather than structured metadata alone. According to the size tag, the corpus sits in the 100K–1M row band, with the published train split listing 467,790 rows.
Structure and fields
Records are organised around five columns: publication_number and publication_date carry identifier and date strings, kind holds the publication-type code (A1), text contains the full extracted document body, and text_len reports its character length as an int32. The flat schema means downstream consumers can filter by publication_number, slice on publication_date, or measure document volume via text_len without joining auxiliary tables. All text content is stored as plain strings, simplifying ingestion with pandas or polars.
How analysts use it
Analysts interested in French innovation activity can scan publication_date and publication_number to track filing cadence or back-fill historical series. The raw text column supports keyword searches, applicant or inventor extraction, and topic modelling to surface emerging technology areas. Because each row is a whole document, text_len is a useful proxy for measuring disclosure complexity when comparing applicants or technology classes.
Documentation & references 1
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