In this task, you will be presented with a context from an academic paper and you have to write an answerable question based on the context. Your questions can be extractive, abstractive, or yes-no questions.

In this work, we analyze a set of tweets related to a specific classical music radio channel, BBC Radio 3, interested in detecting two types of musical named entities, Contributor and Musical Work.
What language is the Twitter content in?

The above pseudocode is agnostic with respect to the choice of fragmentation and environment functions; task-specific choices are described in more detail for each experiment below.

Discussion
Which languages do they test on?

Fortunately, 180221 of 231162 author names could be matched successfully. There are many reasons for the remaining uncovered cases. 9073 Latin names could not be found in the name dictionary ENAMDICT and 14827 name matchings between the names' Latin and kanji representations did not succeed. These names might be missing at all in the dictionary, delivered in a very unusual format that the tool does not cover, or might not be Japanese or human names at all. Of course, Japanese computer scientists sometimes also cooperate with foreign colleagues but our tool expects Japanese names and is optimized for them.

How successful are they at matching names of authors in Japanese and English?