Update README.md

README.md

@@ -859,7 +859,7 @@ MessIRve is a large-scale dataset for Spanish IR, designed to better capture the
 
 Queries are obtained from Google's autocomplete API (www.google.com/complete), and relevant documents are Spanish Wikipedia paragraphs containing answers from Google Search "featured snippets". This data collection strategy is inspired by [GooAQ](https://github.com/allenai/gooaq/tree/main).
 
-The files presented is the qrels. It is presented in a format such that it is easy to be explored, since it includes the queries' and documents' texts. 
+The files presented here are the qrels. The style in which they are displayed makes them easier to explore, as it includes the full texts of documents and queries. 
 
 * For the conventional TREC-style topics and qrels files, refer to https://huggingface.co/datasets/spanish-ir/messirve-trec
 * The corpus of documents that accompanies this dataset is https://huggingface.co/datasets/spanish-ir/eswiki_20240401_corpus
@@ -931,10 +931,13 @@ A typical instance of one subset of the dataset looks like:
 
 We extract queries from Google's autocomplete API for 20 countries with Spanish as an official language, plus the United States. Equatorial Guinea was the only country left out because it doesn't have a Google domain.
 
+Some API results were independent of the country-specific domain, many queries are not specific of any country. These are included under the country label _none_.
 
-Test should always have match_score = 1 and expanded_search = False
+Queries from _none_ were combined with the set of unique queries from all countries and included in the _full_ subset. Unlike the country-specific sets, in the _full_ set some queries can have multiple relevant documents because the same query may return different featured snippets in different country domains. 
 
-For statistics for each subset and split, see the paper.
+The dataset is partitioned into training and test queries in such a way that the Wikipedia article to which the paragraph belongs is present in only one of the splits. The partitioning was done by country, with about 20\% of the articles assigned to the test set. Moreover, test instances always have match_score = 1 and expanded_search = False.
+
+For further detail, such as statistics for each subset and split, see the paper.
 
 
 ## Citation
@@ -943,8 +946,8 @@ For statistics for each subset and split, see the paper.
 
 **BibTeX:**
 
-[More Information Needed]
+TBA
 
 **APA:**
 
-[More Information Needed]
+TBA