 On the other hand , proponents of prototype theory propose that count @-@ classifiers may not have innate definitions , but are associated with a noun that is prototypical of that category , and nouns that have a " family resemblance " with the prototype noun will want to use the same classifier . For example , horse in Chinese uses the classifier 匹 pǐ , as in 三匹马 ( sān pǐ mǎ , " three horses " ) — in modern Chinese the word 匹 has no meaning . Nevertheless , nouns denoting animals that look like horses will often also use this same classifier , and native speakers have been found to be more likely to use the classifier 匹 the closer an animal looks to a horse . Furthermore , words that do not meet the " criteria " of a semantic category may still use that category because of their association with a prototype . For example , the classifier 颗 ( 顆 ) kē is used for small round items , as in 一颗子弹 ( yì kē zǐdàn , " one bullet " ) ; when words like 原子弹 ( yuánzǐdàn , " atomic bomb " ) were later introduced into the language they also used this classifier , even though they are not small and round — therefore , their classifier must have been assigned because of the words ' association with the word for bullet , which acted as a " prototype " . This is an example of " generalization " from prototypes : Erbaugh has proposed that when children learn count @-@ classifiers , they go through stages , first learning a classifier @-@ noun pair only ( such as 条鱼 tiáo yú , CL @-@ fish ) , then using that classifier with multiple nouns that are similar to the prototype ( such as other types of fish ) , then finally using that set of nouns to generalize a semantic feature associated with the classifier ( such as length and flexibility ) so that the classifier can then be used with new words that the person encounters . 
