This paper presents a discovery that the length of the entities in various datasets follows a family of scale-free power law distributions. The concept of entity here broadly includes the named entity, entity mention, time expression, aspect term, and domain-specific entity that are well investigated in natural language processing and related areas. The entity length denotes the number of words in an entity. The power law distributions in entity length possess the scale-free property and have well-defined means and finite variances. We explain the phenomenon of power laws in entity length by the principle of least effort in communication and the preferential mechanism.
According to the review by , first demonstrated that the word length in a corpus empirically and theoretically follows a variant of Poisson distributions. The word length of a natural corpus has been observed to follow the variants of Poisson distributions in more than 32 languages @cite_17 .
@cite_17
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Abstract In this study, word length distributions are investigated in Old Icelandic songs and prose texts. Although Old Icelandic is separated from the other languages studied so far within the framework of the Gottingen word length project, the same model, viz. the hyperPoisson distribution, can successfully be fitted to the data.