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.
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Question: Following previous work BIBREF13, BIBREF12, BIBREF10, BIBREF17, BIBREF9, BIBREF7, we choose SemCor3.0 as training corpus, which is the largest corpus manually annotated with WordNet sense for WSD.

Answer: Is SemCor3.0 reflective of English language data in general?

Question: Trinomials are likely to appear in exactly one order, and when they appear in more than one order the last word is almost always the same across all instances.

Answer: Are there any new finding in analasys of trinomials that was not present binomials?

Question: We train three systems (S1, S2 and S3) with the corpora summarised in Table TABREF5. The first two systems are transformer models trained on different amounts of data (6M vs. 18M parallel sentences as seen in the Table). The third system includes a modification to consider the information of full coreference chains throughout a document augmenting the sentence to be translated with this information and it is trained with the same amount of sentence pairs as S1.

Answer:
Which three neural machine translation systems are analyzed?