Update README.md

README.md

@@ -1,6 +1,5 @@
 ---
-YAML tags:
-
+YAML tags: null
 annotations_creators:
 - no-annotation
 language_creators:
@@ -8,14 +7,13 @@ language_creators:
 language:
 - en
 - nb
-- no
+- 'no'
 - nn
 - sv
 - da
 - is
 - fo
-license:
-- other
+license: cc
 multilinguality:
 - multilingual
 pretty_name: NCC
@@ -24,10 +22,9 @@ size_categories:
 source_datasets:
 - original
 task_categories:
--  text-generation
+- text-generation
 task_ids:
 - language-modeling
-extra_gated_prompt: "The Directive on Copyright in the Digital Single Market, which came into force on June 6 2019, amends the European Union copyright and database legislation and allows for Text and Data Mining (TDM) activities for research organizations and cultural heritage institutions. Under the terms of the aforementioned directive, by clicking on 'Access repository' you agree on using the text and data contained in this dataset for non-commercial scientific purposes only."
 
 ---
 # Dataset Card for NbAiLab/NCC
@@ -57,9 +54,31 @@ extra_gated_prompt: "The Directive on Copyright in the Digital Single Market, wh
 - **Paper:** https://arxiv.org/abs/2104.09617
 - **Point of Contact:** [Freddy Wetjen](mailto:[email protected])
 
-The Norwegian Colossal Corpus is a collection of multiple smaller Norwegian corpuses suitable for training large language models. We have done extensive cleaning on the datasets, and have made them available in a common format. The total size of the NCC is currently 45GB. 
 
-One important part of the corpus was newspapers, among them a corpus called Norsk Aviskorpus. These were distributed also as part of NCC, and released under CC0 and CC-NC-licenses. As of December 2024, the media houses has asked us not to distribute this corpus any more. There are still quite a lot of newspapers available in NCC, but those released under the so called Språkbank-avtalen is not distributed any more.
+---
+<div style="border: 2px solid red; padding: 10px; border-radius: 5px;">
+
+### ⚠️ Important Update (December 2024)
+
+Previously, newspapers were a significant part of the Norwegian Colossal Corpus (NCC), particularly the newspapers distributed under the so called "Språkbank-avtalen". As of December 2024, at the request of media houses, we have ceased distributing newspapers under this agreement, including the "Norsk Aviskorpus." However, NCC still includes numerous newspapers that are released under more open agreements."
+
+</div>
+
+---
+
+The Norwegian Colossal Corpus is a collection of multiple smaller Norwegian corpuses suitable for training large language models. We have done extensive cleaning on the datasets, and have made them available in a common format. The total size of the NCC is currently 30GB. 
+
+## Licenses
+| Corpus                 | License                                                                          |
+|------------------------|----------------------------------------------------------------------------------|
+| Library Newspapers     | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/)                    |
+| Library Books          | [CC0 1.0](https://creativecommons.org/publicdomain/zero/1.0/)                    |
+| LovData CD             | [NLOD 2.0](https://data.norge.no/nlod/en/2.0/)                                    |
+| Government Reports     | [NLOD 2.0](https://data.norge.no/nlod/en/2.0/)                                    |
+| Parliament Collections | [NLOD 2.0](https://data.norge.no/nlod/en/2.0/)                                    |
+| Public Reports         | [NLOD 2.0](https://data.norge.no/nlod/en/2.0/)                                    |
+| Målfrid Collection     | [NLOD 2.0](https://data.norge.no/nlod/en/2.0/)                                    |
+| Wikipedia              | [CC BY-SA 3.0](https://creativecommons.org/licenses/by-sa/3.0/)                  |
 
 
 ## How to Use
@@ -742,4 +761,4 @@ If you are using the corpus, please refer to the articles below:
   languages present in the corpus such as English, Swedish, and Danish. For languages not included in the corpus, the weights degrade moderately while keeping strong multilingual properties. Therefore,
   we show that building high-quality models within a memory institution using somewhat noisy optical character recognition (OCR) content is feasible, and we hope to pave the way for other memory institutions to follow.},
 }
-```
+```