12. 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; determining that the NCC score satisfies a threshold; and in response to determining that the NCC score satisfies the threshold, assigning, to the compound in one or more of the computer readable media, a label that indicates the compound is an NCC.
12. 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; determining that the NCC score satisfies a threshold; and in response to determining that the NCC score satisfies the threshold, assigning, to the compound in one or more of the computer readable media, a label that indicates the compound is an NCC. 14. The method of claim 12 , wherein determining the plurality of measures comprises: generating a corpus occurrence measure of the measures that is based on comparison of: a first indicated quantity of occurrences of the compound in a corpus, and a second indicated quantity of occurrences of an alternate compound in the corpus, the alternate compound being the candidate substitution with the second word.