In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.
--------
Question: We propose a new unsupervised model, Sent2Vec, for learning universal sentence embeddings Formally, we learn a source (or context) embedding INLINEFORM0 and target embedding INLINEFORM1 for each word INLINEFORM2 in the vocabulary, with embedding dimension INLINEFORM3 and INLINEFORM4 as in ( EQREF6 ). The sentence embedding is defined as the average of the source word embeddings of its constituent words, as in ( EQREF8 ). We augment this model furthermore by also learning source embeddings for not only unigrams but also n-grams present in each sentence, and averaging the n-gram embeddings along with the words, i.e., the sentence embedding INLINEFORM5 for INLINEFORM6 is modeled as DISPLAYFORM0 
 Question: How do the n-gram features incorporate compositionality?

Answer: by also learning source embeddings for not only unigrams but also n-grams present in each sentence, and averaging the n-gram embeddings along with the words


Question: Validated transcripts were sent to professional translators. In order to control the quality of the professional translations, we applied various sanity checks to the translations BIBREF11. We also sanity check the overlaps of train, development and test sets in terms of transcripts and voice clips (via MD5 file hashing), and confirm they are totally disjoint. 
 Question: How is the quality of the data empirically evaluated? 

Answer: Validated transcripts were sent to professional translators. various sanity checks to the translations  sanity check the overlaps of train, development and test sets


Question: Therefore, in order to create fair systems it is necessary to take into account the representation problems in society that are going to be encapsulated in the data. 
 Question: What is the goal of investigating NLP gender bias specifically in the news broadcast domain and Anchor role?

Answer:
create fair systems