Statistical Interpretation of Compound Nouns

We present a method for detecting compound nominalisations in open data, and deriving an interpretation for them. Discovering the semantic relationship between the modifier and head noun in a compound nominalisation is first construed as a twoway disamiguation task between an underlying subject or object semantic relation between a head noun and its modifier, and second as a three-way task between subject, direct object, and prepositional object relations. The detection method achieves about 89% recall on a data set annotated by way of Celex and Nomlex, and about 70% recall on a randomly-sampled data set based on the British National Corpus, with 77% recall on detecting a more general set of compound nouns from this data. The interpretation method achieved about 72% accuracy in the two-way task, and 57% in the three-way task, using a statistical measure based on z-scores — the confidence interval — in selecting one of the relations. Our proposed method has the advantage over previous research in that it can act over open data to detect and interpret compound nominalisations, as opposed to only operating in a limited domain or requiring hand-selection or hand-tuning.