Helpful for: MBA and Master’s applicants
Read Time: 6 minutes
- “Winograd Schema Challenge” is a machine intelligence test in multiple choice format which requires a robot to answer specific questions, or schemas, focusing on parts of speech, in order to identify its ability to apply knowledge and reasoning effectively. Consider the simple example Ryan gives, asking us what is big in the sentence, “The trophy would not fit in the brown suitcase because it was too big.” The answer “the trophy” might seem evident to a human, but to a robot it might instead be “the suitcase” or more general “it”. Ryan explains:
All the robot has is structure. It does not have meaning. Sure, the robot might know the dictionary, but true meaning comes from our seeing a combination of words never before encountered, yet still being able to construct a scenario that allows us to understand them.
- What sets our brains apart from those of robots is our ability to dissect complex language and interpret connected words by constructing experimental scenarios. Developing the skill of using our imagination to elicit different contexts a word carries is crucial for excelling on the Verbal section of the GMAT, especially when answering Sentence Correction questions.
- Ryan estimates that a robot might be able to solve 60% of Sentence Correction questions However, the 40% left that could contribute to a great score, are questions which rely on meaning, not grammar.
- Grammar rules are important to know, but they are also complex and often create arguments among linguists. When in doubt while answering GMAT Sentence Correction questions, focus on pinpointing exactly what the sentence is trying to convey.
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Source: Manhattan Prep