In this task, based on the given sentence and the question, you are asked to generate an incorrect answer. The incorrect answer has to be a text span from the given sentence. Note that, the correct answer to the given question will require understanding of coreference resolution. Coreference resolution is the task of clustering mentions in text that refer to the same underlying real world entities. For example let's take a sentence 'I voted for Obama because he was most aligned with my values, she said.' Here in this example 'I', 'my', and 'she' belong to the same cluster and 'Obama' and 'he' belong to the same cluster. Now let's discuss another example , original sentence: 'I voted for Trump because he was most aligned with my values',John said. Now here is the same sentence with resolved coreferences: 'John voted for Trump because Trump was most aligned with John's values',John said. 

Example Input: Sentence: Grace was happy to trade me her sweater for my jacket. She thinks it looks great on her. Question: What looks great on Grace?
Example Output: sweater

Example Input: Sentence: When the sponsors of the bill got to the town hall, they were surprised to find that the room was full of opponents. They were very much in the minority. Question: Who were in the minority?
Example Output: opponents

Example Input: Sentence: The table won't fit through the doorway because it is too wide. Question: What is too wide?
Example Output:
doorway