The language-invariant aspect of compounding: Predicting compound meanings across languages
Authors: Fritz Günther, Marco Marelli (Università di Milano Bicocca, 2018)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In the present study, we invesEnglish. In the present study, we investigated to what extent compounding involves general-level cognitive abilities related to conceptual combination. If that was the case, the compounding mechanism should be largely invariant across different languages. Under this assumption, a compositional model trained on word representations in one language should be able to predict compound meanings in other languages. We investigated this hypothesis by training a word embeddingbased compositional model on a set of plied this model to German and Italian test compounds. The model partially predicted compound meanings in German, but not in Italian.

Introduction
Compounds are complex words such as airport, with two constituents that can be used as free words. Compounding is a highly prevalent phenomenon across many languages. It has been argued to be a proto-linguistic structure to combine simple words into novel and complex concepts, from which more complex compositional language structures have been derived (Jackendoff, 2002). Given the prevalence and ubiquity of compounding across languages, it is reasonable to assume that speakers of different languages rely, to some degree, on the same cognitive mechanisms to compose the meanings of constituents into a compound meaning. Indeed, the linguistic phenomenon of compounding is generally considered to be the linguistic mirror of the cognitive process of conceptual combination (Gagn´e and Spalding, 2009; Murphy, 2002). Thus, while speciﬁc aspects of compounding will inevitably vary between languages due to differences in the language structure and other idiosyncracies, we assume that there is also a language-invariant aspect of compounding that can be transferred across languages. We will investigate this hypothesis by examining whether a compositional model trained on one language (English) is able to predict compound meanings in other languages (German and Italian).

Conclusion
Our results show that a compositional model trained in one language exclusively (English) can be applied to another language (German) to partially predict the meanings of compounds in the latter, of which the model had no training experience at all. Obviously, the model trained on English compounds predicted English compound meanings far better than German compound meanings. This does not stand contrary to our hypothesis: We do not assume that compounding is a tout-court language-invariant mechanism, but that compounding also encompasses general mechanisms besides language-speciﬁc features. However, the model trained on English was not able to predict Italian compound meanings above baseline level. Thus, our results only partially support our hypothesis. In interpreting this ﬁnding, it has to be considered that the Italian evaluation set was far smaller than the English and the German sets, leading to decreased statistical power in this case (note that, on a purely descriptive level, model performance in Italian is slightly above baseline). Keeping that in mind, our results indicate that the applicability of a compositional model across languages seems to depend on the similarity between the language in which a model was trained and the one where it is applied. 1The head is the compound constituent that denotes the semantic category of a word: an airport is a type of port. In structural terms, German is in fact much more similar to English than Italian. Both English and German are West-Germanic languages which almost exclusively produce head-second compounds and have highly productive and very rich compounding systems. Italian compounds however can be head-ﬁrst or head-second, and the compounding system is far less productive in Italian than in English or German (one of the factors responsible for the fact that our Italian item set was smaller than the English or German sets). This explanation is still tentative given the restricted range of languages investigated here. A more thorough investigation on this speciﬁc issue would require tests on a wide range of languages, which should be theoretically characterized in terms of their structural similarity with respect to compounding beforehand. Additionally, future work is required to address other language-dependent aspects of compounding. For example, we focussed only on closedform compounds, while some languages (for example English and Italian, but not German) can produce open forms such as school bus or pesce spada. Another issue to be investigated more closely is headedness. On the one hand, headsecond Italian compounds are more similar to English and German from a structural point of view; on the other hand, head-ﬁrst compounds are assumed to be more like English and German in terms of productivity and regularity of meaning. Although our item set included head-ﬁrst as well as head-second Italian compounds, both are obviously still smaller than the complete Italian item set. Thus, in future studies larger item sets are required to provide such differential tests with the necessary statistical power.