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The Latent Structure of Dictionaries

机译:词典的潜在结构

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How many wordsand which onesare sufficient to define all other words? When dictionaries are analyzed as directed graphs with links from defining words to defined words, they reveal a latent structure. Recursively removing all words that are reachable by definition but that do not define any further words reduces the dictionary to a Kernel of about 10% of its size. This is still not the smallest number of words that can define all the rest. About 75% of the Kernel turns out to be its Core, a Strongly Connected Subset of words with a definitional path to and from any pair of its words and no word's definition depending on a word outside the set. But the Core cannot define all the rest of the dictionary. The 25% of the Kernel surrounding the Core consists of small strongly connected subsets of words: the Satellites. The size of the smallest set of words that can define all the restthe graph's minimum feedback vertex set or MinSetis about 1% of the dictionary, about 15% of the Kernel, and part-Core/part-Satellite. But every dictionary has a huge number of MinSets. The Core words are learned earlier, more frequent, and less concrete than the Satellites, which are in turn learned earlier, more frequent, but more concrete than the rest of the Dictionary. In principle, only one MinSet's words would need to be grounded through the sensorimotor capacity to recognize and categorize their referents. In a dual-code sensorimotor/symbolic model of the mental lexicon, the symbolic code could do all the rest through recombinatory definition.
机译:有多少个单词,哪些足以定义所有其他单词?当将字典作为有向图进行分析时,从定义词到定义词的链接就会显示出潜在的结构。递归地删除定义中可到达但未定义任何其他单词的所有单词,将字典减少到其大小的大约10%的内核。这仍然不是可以定义所有其余单词的最小单词数。大约有75%的内核是其核心,即单词的强连接子集,具有进出其任意一对单词的定义路径,而没有单词的定义取决于该集合之外的单词。但是核心无法定义字典的其余部分。核心周围25%的内核由小的紧密连接的单词子集组成:卫星。可以定义其余所有图的最小反馈顶点集或MinSet的最小单词集的大小约为字典的1%,内核的15%和部分核心/部分卫星。但是每本词典都有大量的MinSet。与卫星相比,学习核心词的时间更早,更频繁,更具体,而与卫星字典相比,卫星的学习时间更早,更频繁但更具体。原则上,仅通过MinSet的单词就可以通过感觉运动能力来进行识别和分类。在心理词典的双代码感觉运动/符号模型中,符号代码可以通过重组定义完成所有其余工作。

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