Many annotation schemes for information structure have been developed in recent years (Calhoun et al., 2005; Paggio, 2006; Goetze et al., 2007; Bohnet et al., 2013; Riester et al., 2018), in line with increased attention on the interaction between discourse and other linguistic dimensions (e.g. syntax, semantics, prosody). However, a crucial issue which existing schemes either gloss over, or propose only crude guidelines for, is how to annotate information structure in complex sentences. This unsatisfactory treatment is unsurprising given that theoretical work on information structure has traditionally neglected its status in dependent clauses. In this paper, I evaluate the status of pre-existing annotation schemes in relation to this vexed issue, and outline certain desiderata as a foundation for novel, more nuanced approaches, informed by state-of-the art theoretical insights (Erteschik-Shir, 2007; Bianchi and Frascarelli, 2010; Lahousse, 2010; Ebert et al., 2014; Matic et al., 2014; Lahousse, 2022). These desiderata relate both to annotation formats and the annotation process. The practical implications of these desiderata are illustrated via a test case using the Corpus of Historical Low German (Booth et al., 2020). The paper overall showcases the benefits which result from a free exchange between linguistic annotation models and theoretical research.

We outline the issues and decisions involved in creating a Penn-style treebank of Middle Low German (MLG, 1200-1650), which will form part of the Corpus of Historical Low German (CHLG). The attestation for MLG is rich, but the syntax of the language remains relatively understudied. The development of a syntactically annotated corpus for the language will facilitate future studies with a strong empirical basis, building on recent work which indicates that, syntactically, MLG occupies a position in its own right within West Germanic. In this paper, we describe the background for the corpus and the process by which texts were selected to be included. In particular, we focus on the decisions involved in the syntactic annotation of the corpus, specifically, the practical and linguistic reasons for adopting the Penn annotation scheme, the stages of the annotation process itself, and how we have adapted the Penn scheme for syntactic features specific to MLG. We also discuss the issue of data uncertainty, which is a major issue when building a corpus of an under-researched language stage like MLG, and some novel ways in which we capture this uncertainty in the annotation.

The development of linguistic corpora is fraught with various problems of annotation and representation. These constitute a very real challenge for the development and use of annotated corpora, but as yet not much literature exists on how to address the underlying problems. In this paper, we identify and discuss five sources of representation problems, which are independent though interrelated: ambiguity, variation, uncertainty, error and bias. We outline and characterize these sources, discussing how their improper treatment can have stark consequences for research outcomes. Finally, we discuss how an adequate treatment can inform corpus-related linguistic research, both computational and theoretical, improving the reliability of research results and NLP models, as well as informing the more general reproducibility issue.

Language change is often assessed against a set of pre-determined time periods in order to be able to trace its diachronic trajectory. This is problematic, since a pre-determined periodization might obscure significant developments and lead to false assumptions about the data. Moreover, these time periods can be based on factors which are either arbitrary or non-linguistic, e.g., dividing the corpus data into equidistant stages or taking into account language-external events. Addressing this problem, in this paper we present a data-driven approach to periodization: ‘DiaHClust’. DiaHClust is based on iterative hierarchical clustering and offers a multi-layered perspective on change from text-level to broader time periods. We demonstrate the usefulness of DiaHClust via a case study investigating syntactic change in Icelandic, modelling the syntactic system of the language in terms of vectors of syntactic change.