Annotating and Disambiguating the Discourse Usage of the Enclitic d A in T urkish (2023)

Abstract: The Turkish particle dA is a focus-associated enclitic, and it can act as a discourse connective conveying multiple senses, like additive, contrastive, causal etc. Like many other linguistic expressions, it is subject to usage ambiguity and creates a challenge in natural language automatization tasks. For the first time, we annotate the discourse and non-discourse connnective occurrences of dA in Turkish with the PDTB principles. Using a minimal set of linguistic features, we develop binary classifiers to distinguish its discourse connective usage from its other usages. We show that despite its ability to cliticize to any syntactic type, variable position in the sentence and having a wide argument span, its discourse/non-discourse connective usage can be annotated reliably and its discourse usage can be disambiguated by exploiting local cues.

## introduction discourse connectives are one of the most important aspects of discourse structure. they are lexicosyntactic elements that signal a pragmatic or semantic relation @xcite between two discourse units such as verb phrases, clauses or sentences @xcite . while the most well-known discourse connectives belong to syntactic classes such as coordinating and subordinating conjunctions @xcite , adverbs (however) or prepositional phrases (in sum), it is known that clitics can also function similarly as discourse connectives @xcite , and may convey additive, contrastive or concessive senses @xcite . clitics are particles that are phonologically dependent on the lexical item to which they are attached and in many languages, they play a role in expressing focus. usually, all types of phrases (noun phrases, verb phrases, etc.) can function as foci of a particle. in turkish, too, most clitics are attached to phrases. the enclitic da is a special particle, which is both focus-and topic-associated. in this respect, da (orthographically "de", "da") is even more worth investigating. 1 the focus-sensitive characteristics and the discourse connective role of da have long been noticed in the turkish linguistics literature @xcite @xcite . however, its discourse connective usage has not been annotated in the existing discourse-level turkish corpora and, to the best of our knowledge, it has not been the topic of a computational discourse analysis so far. the existing experiments are limited to the disambiguation of the orthographic forms da (one of the representations of da) and -da (one of the representations of the locative suffix, -da) @xcite . 2 it is known that connectives are susceptible to usage ambiguity, that is "whether or not a given token is serving as a discourse connective in its context" @xcite , and this has initiated usage disambiguation tasks over connectives in many languages. well-known works that disambiguate english connectives involve @xcite and @xcite . similar tasks have been carried out in chinese @xcite , french @xcite , german @xcite and turkish @xcite . to facilitate natural language processing (nlp) tasks such as text summarization, automatic translation, knowledge extraction, etc., usage ambiguity tasks have to involve clitics as well as other types of discourse connectives. given that there is a research gap in the usage disambiguation of da in particular and turkish clitics in general, this paper describes an annotation study followed by a classification task over a corpus where da's various non-discourse connective roles are distinguished from its discourse connective roles. the summary of our contributions are: the outline of the paper is as follows: section 2 focuses the linguistic behavior of da. it provides a description of its various functions demonstrating its usage ambiguity. in section 3, the data creation stage of our work is described, the annotation style and inter-annotator agreement results are presented. in section 4, we describe our experimental setup by introducing the feature set, data processing (e.g. lemmatization, tagging) and the classification algorithms we used. an evaluation of the success of the models and an error analysis are presented. in section 5, we summarize our work also discussing its limitations and contributions, and offer some ideas for future work. ## background turkish is a verb-final, agglutinating language, where suffixation plays an important role both in derivation and inflection. it has clitics such as mi (the marker of yes/no questions), (y)di and (y)miş (copular markers), and da. an important grammatical fact that teases apart clitics and affixes is that while clitics can attach to material already containing clitics, affixes cannot @xcite . ## conclusion, limitations and further work our work has two main parts; in the first part, we worked on a challenging annotation task not targeted before in turkish nlp: the task of how the multi-faceted clitic da can be annotated for its discourse and non-discourse connective usage. in the second part, we showed that with an ml approach, we can achieve success rates of an average of 0.77 in disambiguating the usage of da. however, our work is not without its limitations; for example, it is limited by the size of the corpus. it is assumed that as the dataset grows, more linguistic features of a discourse connective can be attested @xcite . secondly, we are aware that the linguistic features we used in the ml experiments are not novel, but we believe we have shown that with a minimal set of rules, we can reach promising results in disambiguating the usage of da. our work not only contributes to turkish but also to discourse studies in general as we have brought to light the discourse role of a clitic through an annotation study and a computational analysis. it is therefore hoped to set the stage for other languages that have clitics with a discourse function. the results presented here can be used as a benchmark for turkish clitics, and they can serve as a reference point for other languages that have clitics with a discourse function.