Align README with approved BEIR template

Use exact shared README template; rename 'NFCorpus Data Splits' to dataset-specific '<X> Data Splits'.

README.md

@@ -79,7 +79,17 @@ dataset_info:
 
 BEIR is a heterogeneous benchmark built from 18 diverse datasets representing 9 information retrieval tasks.
 
-This `webis-touche2020` subset is part of BEIR.
+- Fact-checking: [FEVER](http://fever.ai), [Climate-FEVER](http://climatefever.ai), [SciFact](https://github.com/allenai/scifact)
+- Question-Answering: [NQ](https://ai.google.com/research/NaturalQuestions), [HotpotQA](https://hotpotqa.github.io), [FiQA-2018](https://sites.google.com/view/fiqa/)
+- Bio-Medical IR: [TREC-COVID](https://ir.nist.gov/covidSubmit/index.html), [BioASQ](http://bioasq.org), [NFCorpus](https://www.cl.uni-heidelberg.de/statnlpgroup/nfcorpus/)
+- News Retrieval: [TREC-NEWS](https://trec.nist.gov/data/news2019.html), [Robust04](https://trec.nist.gov/data/robust/04.guidelines.html)
+- Argument Retrieval: [Touche-2020](https://webis.de/events/touche-20/shared-task-1.html), [ArguAna](tp://argumentation.bplaced.net/arguana/data)
+- Duplicate Question Retrieval: [Quora](https://www.quora.com/q/quoradata/First-Quora-Dataset-Release-Question-Pairs), [CqaDupstack](http://nlp.cis.unimelb.edu.au/resources/cqadupstack/)
+- Citation-Prediction: [SCIDOCS](https://allenai.org/data/scidocs)
+- Tweet Retrieval: [Signal-1M](https://research.signal-ai.com/datasets/signal1m-tweetir.html)
+- Entity Retrieval: [DBPedia](https://github.com/iai-group/DBpedia-Entity/)
+
+> **This `webis-touche2020` subset is the Argument Retrieval task within BEIR.**
 
 ### Languages
 
@@ -132,16 +142,14 @@ qrels = {
 }
 ```
 
-### Data Splits
+### Touche-2020 Data Splits
 
 | Subset | Split | Rows |
 | --- | --- | ---: |
 | corpus | corpus | 382,545 |
 | queries | queries | 49 |
 
-### NFCorpus Data Splits
-
-- `train`, `dev`, `test`
+### BEIR Direct Download
 
 You can also download BEIR datasets directly (without loading through Hugging Face datasets) using the links below.