metadata
license: cc-by-3.0
Dataset Summary
- Homepage: https://sites.google.com/view/salt-nlp-flang
- Models: https://huggingface.co/SALT-NLP/FLANG-BERT
- Repository: https://github.com/SALT-NLP/FLANG
FLUE
FLUE (Financial Language Understanding Evaluation) is a comprehensive and heterogeneous benchmark that has been built from 5 diverse financial domain specific datasets.
Sentiment Classification: Financial PhraseBank
Sentiment Analysis, Question Answering: FiQA 2018
New Headlines Classification: Headlines
Named Entity Recognition: NER
Structure Boundary Detection: FinSBD3
Dataset Structure
The FiQA dataset has a corpus, queries and qrels (relevance judgments file). They are in the following format:
corpus
file: a.jsonl
file (jsonlines) that contains a list of dictionaries, each with three fields_id
with unique document identifier,title
with document title (optional) andtext
with document paragraph or passage. For example:{"_id": "doc1", "title": "Albert Einstein", "text": "Albert Einstein was a German-born...."}
queries
file: a.jsonl
file (jsonlines) that contains a list of dictionaries, each with two fields_id
with unique query identifier andtext
with query text. For example:{"_id": "q1", "text": "Who developed the mass-energy equivalence formula?"}
qrels
file: a.tsv
file (tab-seperated) that contains three columns, i.e. thequery-id
,corpus-id
andscore
in this order. Keep 1st row as header. For example:q1 doc1 1