Update README.md

README.md

@@ -23,8 +23,6 @@ Zelai-Handi: A Large Open Dataset to Feed the next Gen of Basque LLMs
 <!-- Provide a longer summary of what this dataset is. -->
 
 - **Curated by:** Orai NLP Technologies
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
 - **Language(s) (NLP):** EU
 - **License:** CC
 - 
@@ -61,7 +59,7 @@ The corpus is released in jsonl format. Each document contains the following pro
         "title": "document title", 
         "author": "document author if known, source otherwise", 
         "date": "yyyy-mm-dd", 
-        "text": "document content, ready to use raw text. Title text is included as well.",
+        "text": "document content, ready to use raw text. Title text (for news and articles) is included as well.",
         "domain": "document domain. one of ['news', 'administrative', 'wikipedia', 'science', 'subtitles', 'literature', 'videogames']"
 }
 ```
@@ -114,6 +112,8 @@ Data collection efforts were performed between 2024/01/01-2024/02/23.
 
 [More Information Needed]
 
+Hemen source guztiak zerrendatuko nituzke, tokikom-en kasuan, barruko guztiak zerrendatuz.
+
 #### Personal and Sensitive Information
 
 The dataset contains publicly available data that might be considered personal and sensitive (e.g., data that reveals addresses, uniquely identifiable names or aliases, racial or ethnic origins, sexual orientations, religious beliefs, political opinions, financial or health data, etc.).
@@ -123,7 +123,7 @@ The dataset contains publicly available data that might be considered personal a
 ## Bias, Risks, and Limitations
 
 <!-- This section is meant to convey both technical and sociotechnical limitations. -->
-This corpus inherits the Basque speaking society's stereotypes (gender bias, ethnical bias, cultural bias, linguistic bias, ...).
+This corpus inherits the Basque speaking society's stereotypes (gender bias, ethnical bias, cultural bias, linguistic bias, ...), and it contains fictional text (literature and subtitles).
 
 <!--Furthermore, text coming from susa (literature) and subtitles sources, contain hate speech, slurs or explicit language.
 We decided to include them in the corpus, to ensure that the corpus contains conversational data.
@@ -135,12 +135,10 @@ We did not perform any cleaning or censoring of those, since it might be needed
 <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
 Users should be made aware of the risks, biases and limitations of the dataset. 
-We suggest filtering sources containing hate speech, slurs or explicit language before pretraining an LLM for end tasks like interactive chat.
+We suggest filtering sources as literature and subtitles that might contain hate speech, slurs or explicit language before pretraining an LLM for end tasks like interactive chat.
 
 ## Citation
 
-<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->
-
 <!--We plan to release a paper soon, but, for now, please, cite as follows:
 
 **BibTeX:**