Dieci sfumature di marcatezza sintattica:verso una nozione computazionale di complessità
Authors: Erica Tusa, Felice Dell'Orletta, Simonetta Montemagni, Giulia Venturi (Università di Pisa, CNR-ILC, 2016)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In this work we will investigate whether and as algorithms typically used to evaluate the reliability of the analysis produced by automatic syntactic annotation tools can be used to study the correlation between computational complexity and the linguistic notion of marking. The results achieved, although still preliminary, show the key role of factors such as the orientation of the relationship and the length of dependence in defining the various smudges of the same relationship.

Introduction
Since the 1980s, the belief has been affirmed that methods and techniques developed within computational linguistics could help advance research by providing new evidence for the study of key notions of theoretical linguistics. "Computational linguistics provides important potential tools for the testing of theoretical linguistic constructs and of their power to predict actual language use': this opens the contribution of AUTHOR, which based on the correlation between brandness and frequency proposes the results of an computational study of the notion of brandness at lexical and grammatical level conducted on the Brown corpus. While the evidence collected confirms the expected correlation between frequency and marking, interesting cases are recorded in which the statistical evidence from the Brown Corpus offers both greater problems and greater insight. [...] The frequency data is [...] the reverse of what one might have assumed under the markedness analysis'. Today, more than 40 years after AUTHOR's pionestic study, which was based on a morpho-syntactically noted corpus of about a million words, it is possible to extract accurate and varied linguistic information from the body of far greater dimensions. The increasing reliability of automatic language processing tools is making possible the acquisition of quantitative and computational evidence that spans through different levels of linguistic description, including the syntactical one, which can contribute significantly to the study of open questions of linguistic literature: AUTHOR represents an important example of this renewed line of studies. Within the framework outlined above, the objective of this contribution is to verify whether and to what extent algorithms for identifying the reliability and plausibility of syntactic annotation can contribute to the study of a linguistic phenomenon such as marking. With the increasingly widespread use of addiction syntactic annotations as a starting point for a wide range of applications aimed at extracting information from vast documentary collections, these algorithms arise from the need to identify within the automatically produced annotations the correct ones or, more simply, characterized by a greater degree of reliability and plausibility. This type of assessment can be carried out in relation to both the entire syntactic tree assigned to the single sentence (see Table 1). For example, AUTHOR and AUTHOR), both to the individual dependency relationship (see, among others, AUTHOR and AUTHOR). In this study, we will focus on the second type of algorithms, that is those that operate at the level of the single dependency relationship, to verify the potential in the study of the notion of linguistic brandness. Although these algorithms typically operate on AUTHOR's automatically recorded body, they are also used on body with manually validated annotation (qualified as "gold'): in this case, the aim is to identify errors and inconsistencies of AUTHOR's annotation. The result of these algorithms varies from a binary classification of dependence (correct vs. wrong) as in AUTHOR, to a ordering of relationships according to the reliability and plausibility of the analysis, as proposed by AUTHOR. Beyond differences at the level of the algorithm used and the type of result, in all cases an extensive inventory of selected language characteristics as indicators of complexity is used.

Conclusion
In this study we have explored the hypothesis that algorithms developed to evaluate the reliability and plausibility of syntactic annotations with dependencies produced automatically can provide useful evidence for a reflection around the theme of syntactic complexity, and in particular to reconstruct 'smoothness' of increasing brandiness in relation to the same relationship of dependence. The first results achieved are encouraging: what has been observed in relation to the distribution of dependencies through the bands leads us to assume a strong correlation between the computational complexity of the analysis identified by LISCA and the notion of syntactic brandness. In particular, the role of factors such as relationship orientation and length of dependence has been investigated, with results clearly showing that an algorithm such as LISCA can also be a valid tool for linguistic analysis. Through the analysis of the distribution of dependency relationships in the bands defined on the basis of the order of LISCA it was possible not only to discriminate between marked and unmarked constructions (typically recoverable on the basis of frequency), but also to identify -- relationship by relationship -- the factors that contributed to making it marked. If the orientation of the relationship plays a crucial role in the case of amod, in the case of nsubj it is rather the distance between the head and the employee to determine the marking of the construction. Obviously, this analysis methodology should be extended to the wide range of language characteristics considered. The current developments of this work include: the extension, beyond the length and orientation of the relationship, of the type of linguistic factors explored, to arrive also at the study of the impact of lexical factors; the extension of the type of construction analysed, which could also include combinations of dependencies corresponding to syntactical sub-trees. We believe that the methodology should also be applied to treebanks of different languages, as well as different textual genres within the same language.