..ooo T-Mobile 1:30 PM 52% Norton ZAPS 2e digital wwnorton.com ZAPS Sentence Ver
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..ooo T-Mobile 1:30 PM 52% Norton ZAPS 2e digital wwnorton.com ZAPS Sentence Verification tuf25965@temple.edu Introduction Experience Your Data Discussion INTRODUCTION Think back to your childhood. Your parents probably showed you picture books and named the objects depicted in the illustrations: chicken, blue jay, dog, donkey, goldfish, salmon, whale, chair, desk, clock....After going over the books several times, your parents would start asking you questions about the pictures: "What is this?" or "Which color is that? Not only did you learn the specific labels for the objects, but you could also identify new birds or fish or furniture that you hadn't seen before. That is, you developed a knowledge network of the features that were important for identifying each category; the large, six-foot-high piece of furniture in a neighbor's home was still a clock-just like your toy watch-because it had a round face with numbers. How did you, as a child (and now as an adult with even more complex category knowledge) store all this information? When asked questions about this knowledge, how were you able to retrieve it? This ZAPS lab explores our semantic category knowledge-general knowledge of facts, ideas, meanings and concepts. For instance, how do we store all the information about which animals are birds, and the kinds of features that all birds share? And how do we retrieve this knowledge when called upon to do so? Rather than just verifying that sentences are true or false, this ZAPS lab aims to determine how your semantic category knowledge is structured.Explanation / Answer
Ans1. a. Collin and Quillian used sentence verification tasks to find, How do we organise information about concepts & categories in long term memory and from the responses they created a model for knowledge network in animals.
Ans2. c. Is shorter than semantic distance between canary and animal. Because semantic distance between two words in network is the shortest interval between them. So semantic distance between canary & bird = 1 and semantic distance between canary and animal = 2
Ans3. b. Because the concept "has skin" is stored two levels up (in the category animal), whereas the concept "yellow" is stored at the canary level only, so there is more semantic distance between "canary and has skin" than "canary and yellow"
Ans4. a. It doesn't account for typicality effects. Since the Collins and Quillian model can't explain why some examples are more typical & strongly connected to a category than others. For e.g. a robin is more relatable to the category bird than chicken.
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