1. A method implemented by one or more processors, comprising: identifying, from one or more computer readable media, a compound that comprises at least a first word and a second word; for each of a plurality of candidate substitutions for the first word: determining a plurality of measures that each indicate plausibility of substitution of the candidate substitution for the first word, and generating a score for the candidate substitution based on the plurality of measures; generating an extended substitution score for the compound based on the scores for the candidate substitutions; generating a distributional anomaly score for the compound, generating the distributional anomaly score comprising: generating an estimated embedding vector for the compound based on a generated first word embedding vector of the first word and a generated second word embedding vector of the second word, generating an observed embedding vector for the compound based on application of the compound to a trained embedding model, and generating the distributional anomaly score based on comparison of the estimated embedding vector and the observed embedding vector; generating a non-compositional noun compound (NCC) score for the compound based on both the extended substitution score and the distributional anomaly score; storing, in one or more of the computer readable media, an assignment of the NCC score, or a label generated based on the NCC score, to the compound; subsequent to the storing: receiving a search query that includes the compound and that is submitted via a client computing device; determining the compound is an NCC based on the stored NCC score or the stored label; in response to determining the compound is an NCC, treating the compound as a cohesive unit in identifying content that is responsive to the search query; and in response to the search query, providing the content for presentation via the client computing device.