From f5bf8661b90e9c550391b5074e2cea3be5768ea8 Mon Sep 17 00:00:00 2001 From: Clemens Neudecker Date: Wed, 20 Nov 2019 01:10:43 +0100 Subject: [PATCH] Update Preprocessing.md --- docs/Preprocessing.md | 2 ++ 1 file changed, 2 insertions(+) diff --git a/docs/Preprocessing.md b/docs/Preprocessing.md index b5e4b1f..f249996 100644 --- a/docs/Preprocessing.md +++ b/docs/Preprocessing.md @@ -14,6 +14,8 @@ OCR is based on [OCR-D](https://github.com/OCR-D)'s [ocrd_tesserocr](https://git ### Tokenization +[Transformation](https://github.com/qurator-spk/neath/tree/master/tools) of [PAGE-XML](https://github.com/PRImA-Research-Lab/PAGE-XML) to [TSV](https://github.com/qurator-spk/neath/blob/master/docs/User_Guide.md#data-format). + ### Named Entity Recognition For Named Entity Recognition, a [BERT-Base](https://github.com/google-research/bert) model was trained for noisy OCR texts with historical spelling variation. [sbb_ner](https://github.com/qurator-spk/sbb_ner) is using a combination of unsupervised training on a large (~2.3m pages) [corpus of German OCR](https://zenodo.org/record/3257041) in combination with supervised training on a small (47k tokens) [annotated corpus](https://github.com/EuropeanaNewspapers/ner-corpora/tree/master/enp_DE.sbb.bio). Further details are available in the [paper](https://corpora.linguistik.uni-erlangen.de/data/konvens/proceedings/papers/KONVENS2019_paper_4.pdf).