readme: first draft

README.md

@@ -6,3 +6,81 @@ language:
 # HisGermaNER: NER Datasets for Historical German
 
 In this repository we release another NER dataset from historical German newspapers.
+
+## Newspaper corpus
+
+In the first release of our dataset, we select 11 newspapers from 1710 to 1840 from the Austrian National Library (ONB), resulting in 100 pages:
+
+| Year | ONB ID             | Newspaper                        | URL                                                                      | Pages |
+| ---- | ------------------ | -------------------------------- | ------------------------------------------------------------------------ | ----- |
+| 1720 | `ONB_wrz_17200511` | Wiener Zeitung                   | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=wrz&datum=17200511) | 10    |
+| 1730 | `ONB_wrz_17300603` | Wiener Zeitung                   | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=wrz&datum=17300603) | 14    |
+| 1740 | `ONB_wrz_17401109` | Wiener Zeitung                   | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=wrz&datum=17401109) | 12    |
+| 1770 | `ONB_rpr_17700517` | Reichspostreuter                 | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=rpr&datum=17700517) | 4     |
+| 1780 | `ONB_wrz_17800701` | Wiener Zeitung                   | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=wrz&datum=17800701) | 24    |
+| 1790 | `ONB_pre_17901030` | Preßburger Zeitung               | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=pre&datum=17901030) | 12    |
+| 1800 | `ONB_ibs_18000322` | Intelligenzblatt von Salzburg    | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=ibs&datum=18000322) | 8     |
+| 1810 | `ONB_mgs_18100508` | Morgenblatt für gebildete Stände | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=mgs&datum=18100508) | 4     |
+| 1820 | `ONB_wan_18200824` | Der Wanderer                     | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=wan&datum=18200824) | 4     |
+| 1830 | `ONB_ild_18300713` | Das Inland                       | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=ild&datum=18300713) | 4     |
+| 1840 | `ONB_hum_18400625` | Der Humorist                     | [Viewer](https://anno.onb.ac.at/cgi-content/anno?aid=hum&datum=18400625) | 4     |
+
+## Data Workflow
+
+In the first step, we obtain original scans from ONB for our selected newspapers. In the second step, we perform OCR using [Transkribus](https://readcoop.eu/de/transkribus/).
+
+We use the [Transkribus print M1](https://readcoop.eu/model/transkribus-print-multi-language-dutch-german-english-finnish-french-swedish-etc/) model for performing OCR.
+Note: we experimented with an existing NewsEye model, but the print M1 model is newer and led to better performance in our preliminary experiments.
+
+Only layout hints/fixes were made in Transkribus. So no OCR corrections or normalizations were performed.
+
+We export plain text of all newspaper pages into plain text format and perform normalization of hyphenation and the `=` character.
+After normalization we tokenize the plain text newspaper pages using the `PreTokenizer` of the [hmBERT](https://huggingface.co/hmbert) model.
+
+After pre-tokenization we import the corpus into Argilla to start the annotation of named entities.
+Note: We perform annotation at page/document-level. Thus, no sentence segmentation is needed and performed.
+In the annotation process we also manually annotate sentence boundaries using a special `EOS` tag.
+
+The dataset is exported into an CoNLL-like format after the annotation process.
+The `EOS` tag is removed and the information of an potential end of sentence is stored in a special column.
+
+## Annotation Guidelines
+
+We use the same NE's (`PER`, `LOC` and `ORG`) and annotation guideline as used in the awesome [Europeana NER Corpora](https://github.com/cneud/ner-corpora).
+
+Furthermore, we introduced some specific rules for annotations:
+
+* `PER`: We include e.g. `Kaiser`, `Lord`, `Cardinal` or `Graf` in the NE, but not `Herr`, `Fräulein`, `General` or rank/grades.
+* `LOC`: We excluded `Königreich` from the NE.
+
+## Dataset Format
+
+Our dataset format is inspired by the [HIPE-2022 Shared Task](https://github.com/hipe-eval/HIPE-2022-data?tab=readme-ov-file#hipe-format-and-tagging-scheme).
+Here's an example of an annotated document:
+
+```txt
+TOKEN	NE-COARSE-LIT	MISC
+
+-DOCSTART-	O
+
+# onb:id = ONB_wrz_17800701
+# onb:image_link = https://anno.onb.ac.at/cgi-content/anno?aid=wrz&datum=17800701&seite=12
+# onb:page_nr = 12
+# onb:publication_year_str = 17800701
+den	O	_
+Pöbel	O	_
+noch	O	_
+mehr	O	_
+in	O	_
+Harnisch	O	_
+.	O	EndOfSentence
+Sie	O	_
+legten	O	_
+sogleich	O	_
+```
+
+Note: we include a `-DOCSTART-` information to e.g. allow document-level features for NER as proposed in the [FLERT](https://arxiv.org/abs/2011.06993) paper.
+
+## Dataset Splits
+
+For training powerful NER models on the dataset, we manually splitted the dataset into training, development and test splits.