Sentiment does not correspond to currency pair in filter.

@azzopardic So this is essentially an NLP (Natural Language Processing) and classification problem set - not really an API issue. So if I am right you are looking to separate articles that only talk about one currency pair and ignore articles that mention more than one currency pair. In this case you would need to download the news story and then scan for mentions of any other pairs (ie you should have a list of all pairs) and then only pass the news item to the sentiment engine if only the pair you are referring to is mentioned or you could say then weight the sentiment of the article according to the number of mentions of a currency pair - please see the following example:

from IPython.display import HTML
from bs4 import BeautifulSoup

df = ek.get_news_headlines('GBP=',count=100)
df

this returns us a list of headlines and storyIds. So we then download a news story like this:

We could then count the number of mentions of particular phrases - in our case from currency pairs or rics even:

fx_list = ['GBP','JPY','USD','EUR','EUR/GBP','GBP/EUR']


for fx in fx_list:
    soup = BeautifulSoup(story,"html")
    wordcount = sum(fx == word for word in soup.get_text().split())
    print(fx, wordcount)

So once you have this data you could then decide whether the article was more about one pair or more about other pairs. I don't think this would be the holy grail but its a simple way for you to perhaps experiment a bit to see how things are working in real life. I hope this simple sample can help.