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: I tried to paint a picture of an orchard, with lemons in the lemon trees, but they came out looking more like telephone poles. Question: What looked like telephone poles?
Example Output: lemons

Example Input: Sentence: Jane knocked on Susan's door but she did not get an answer. Question: Who did not get an answer?
Example Output: Susan

Example Input: Sentence: Joe paid the detective after he delivered the final report on the case. Question: Who delivered the final report?
Example Output:
Joe