We investigate the influence of information status ( IS ) on constituent order in German , and integrate our findings into a loglinear surface realisation ranking model . We show that the distribution of pairs of IS categories is strongly asymmetric . Moreover , each category is correlated with morphosyntactic features , which can be automatically detected . We build a loglinear model that incorporates these asymmetries for ranking German string realisations from input LFG F-structures . We show that it achieves a statistically significantly higher BLEU score than the baseline system without these features . There are many factors that influence word order , e.g. humanness , definiteness , linear order of grammatical functions , givenness , focus , constituent weight . In some cases , it can be relatively straightforward to automatically detect these features ( i.e. in the case of definiteness , this is a syntactic property ) . The more complex the feature , the more difficult it is to automatically detect . It is common knowledge that information status1 ( henceforth , IS ) has a strong influence on syntax and word order ; for instance , in inversions , where the subject follows some preposed element , Birner ( 1994 ) reports that the preposed element must not be newer in the discourse than the subject . We would like to be able to use information related to IS in the automatic generation of German text . Ideally , we would automatically annotate text with IS labels and learn from this data . Unfortunately , however , to date , there has been little success in automatically annotating text with IS . We believe , however , that despite this shortcoming , we can still take advantage of some of the insights gained from looking at the influence of IS on word order . Specifically , we look at the problem from a more general perspective by computing an asymmetry ratio for each pair of IS categories . Results show that there are a large number of pairs exhibiting clear ordering preferences when co-occurring in the same clause . The question then becomes , without being able to automatically detect these IS category pairs , can we , nevertheless , take advantage of these strong asymmetric patterns in generation . We investigate the ( automatically detectable ) morphosyntactic characteristics of each asymmetric IS pair and integrate these syntactic asymmetric properties into the generation process . The paper is structured as follows : Section 2 outlines the underlying realisation ranking system for our experiments . Section 3 introduces information status and Section 4 describes how we extract and measure asymmetries in information status . In Section 5 , we examine the syntactic characteristics of the IS asymmetries . Section 6 outlines realisation ranking experiments to test the integration of IS into the system . We discuss our findings in Section 7 and finally we conclude in Section 8 . In this paper we presented a novel method of including IS into the task of generation ranking . Since automatic annotation of IS labels themselves is not currently possible , we approximate the IS categories by their syntactic characteristics . By calculating strong asymmetries between pairs of IS labels , and establishing the most frequent syntactic characteristics of these asymmetries , we designed a new set of features for a log-linear ranking model . In comparison to a baseline model , we achieve statistically significant improvement in BLEU score . We showed that these improvements were not only due to the effect of purely syntactic asymmetries , but that the IS asymmetries were what drove the improved model .

Challenge: While it is known that information status has a strong influence on syntax and word order, its automatic annotation has not been successful.
Approach: They propose to integrate syntactic asymmetric properties of information status into a log-linear model to generate German by approximating their category pairs by syntactic characteristics.
Outcome: The proposed approach achieves a higher BLEU score than the baseline system, not only by the effect of purely syntactic asymmetries but of information status.