New syntactic insights for automated W olof U niversal D ependency parsing (2022)

Abstract: Focus on language-specific properties with insights from formal minimalist syntax can improve universal dependency (UD) parsing. Such improvements are especially sensitive for low-resource African languages, like Wolof, which have fewer UD treebanks in number and amount of annotations, and fewer contributing annotators. For two different UD parser pipelines, one parser model was trained on the original Wolof treebank, and one was trained on an edited treebank. For each parser pipeline, the accuracy of the edited treebank was higher than the original for both the dependency relations and dependency labels. Accuracy for universal dependency relations improved as much as 2.90%, while accuracy for universal dependency labels increased as much as 3.38%. An annotation scheme that better fits a language’s distinct syntax results in better parsing accuracy.

## introduction wolof is a language of senegal, where it is the lingua franca in a nation of more than twelve million people @xcite . about six million speak wolof as their first language @xcite . however, it is severely underrepresented in print, as well as in digital format. because french is the official language of the senegalese state, writing is more commonly practiced in french, while wolof and other indigenous languages are used more in spoken communication. out of the almost 120 languages for which there are universal dependency treebanks available, only eight are indigenous african languages foot_0 . african languages in particular are not well represented, given africa's large share of the world's languages and the relatively large populations of even minority language groups. the presence of these annotated treebanks is promising for automated computational tasks, though. the aim of this study is to improve universal dependency (ud) parsing for wolof. a ud treebank by cheikh @xcite is available for the wolof language. the innovation proposed here is not only to train a parser, as (dione, 2020) has already designed a wolof language-specific parser. the purpose was to determine whether out-of-the-box parsers would show improvement on the wolof treebanks after edits to the part of speech and universal dependency syntax annotations. improved wolof parser models may be used to inform other african language parsers, whose features can be analyzed on their own terms rather than through the lens of other major languages or existing annotation schemes. ## hypothesis the assignment of syntactic dependencies in the wolof ud treebank is based on syntactic and morphological analysis from lexical functional grammar @xcite . in some cases, natural language processing has ignored language-specific features, a sacrifice that is to some degree necessary to create a universal system like ud syntax. this is especially true of languages with less presence in scholarly literature, where tagging or parsing assignments attempt to fit languages into the mold of world languages like english @xcite . the dependency structures of determiners, pronouns, and copulas in the wolof ud treebank comply with the traditional functions of those catgories, but can be realigned to capture broader linguistic generalizations of their behavior while improving accuracy. ## methods the original data in the wolof ud treebank (dione, 2019) consists of 42,832 tokens across 2,107 sentences. these sentences are from four different wolof sources online: the organisation sénégalaise dappui au développement (senegalese aid and development organization) web site, wolof online, wolof wikipedia, and the news site xibaaryi. they were divided by dione into training, test, and development sets. using python, the test, development, and test files of the wolof ud treebank were edited to assign certain lemmas new tags in certain environments and assign new ud labels and hierarchies. ## results accuracy was improved for the models made for each parser pipeline; the spacy and the treetag-ger+malt parser pipelines. relative clauses pronouns were relabeled as determiners (det), which show an increase in recall and f1-score. as relative clause pronouns were made determiner dependents of the relative clause verb, and no longer confused with subjects (nsubj), objects (obj), obliques (obl), and indirect objects (idobj), their precision, recall and f1-scores increase in the improved parser. there are no copula dependency labels in the improved parser, and the relabeling of 182 copulas in the auxiliary (aux) category resulted in an increase in precision, recall, and f1-score for auxiliaries (aux). ## analysis overall, adopting a unified and streamlined syntactic approach to assigning ud relations improves accuracy in wolof. two different parsers both showed improvement in parsing when a def tag was added to definite noun modifiers, headless relative clauses had the same structure as headed ones, and copulas were relabeled to capture their universal function. this suggests that improved accuracy was not simply due to the parsers. the results supported the hypothesis that a unified ud syntax for headed and headless relative clauses improves the accuracy in parsing universal dependencies and their labels. the hypothesis that treating definites as one part of speech category would improve parsing was supported by the results. the hypothesis the relative pronoun is a complementizer due to theoretical syntactic analysis was not supported by the data. in fact, the model that treats the relative pronoun as det, an extracted determiner, results in more accurate parsing. the copular analysis carried over from english does not seem to 'fit' wolof. the data from wolof does not contradict an analysis where di and its allomorphs universally indicates imperfect aspect, rather than acting in some instances as a copula. the subject and object focus morphemes are the same whether the sentence is copular or not, suggesting that they are not copulas in copular sentences. the copula should be instead attributed to some null morpheme. improved parsing accuracy resulting from the reassigning of copula tags and dependency relations in the wolof ud treebank supports this hypothesis. as (dione, 2019) mentions, the morphosyntactic assignments of the wolof ud treebanks, and the universal dependency program in general, are based on lexical functional grammar. in this view, whatever lexical item is the semantic head of the relative clause must have the rest of the relative clause as its dependents. the same is true for morphemes that were labeled as copulas; the subject, object and other arguments of the sentence would be dependents of this morpheme. in other cases, however, the same lexical item would be swapped and the dependency relationship completely inversed. these cases involve the same lexical items, but apply the semantic role of another missing element to them. by adopting syntactic assumptions from the minimalist syntax formalism @xcite , a unified structure can be preserved with the ud framework. the minimalist framework allows for the assumption that the missing element is simply not overtly pronounced. although common in many languages, the need for a copular verb or overt relative clause head need not outweigh the evidence that verbs or relative clause heads may simply be null items. a legitimate ud structure can still be attained while maintaining a consistent roll for these words. such consistency better reflects the findings of (tovey, 2019) that languagespecific particularities should not be diluted in annotation to accommodate more commonly analyzed languages. as editing the treebanks improves parsing from the baseline, the morphological and syntactic annotations made here should improve future parsers. (dione, 2020) trained a wolof-specific lexical functional grammar parser with 67% recall, 93% precision and an f-score of 78%. the most accurate parser model in this study had 78% recall, 78% precision, and an f-score of 78%. the significance of this study is not the accuracy of the parser itself, but the improvement from the baseline. the baseline-trained spacy parser had 76% recall, 76% precision, and an f-score of 76%, meaning that each measure improved by 2%. this improvement should carry over if implemented with future wolof ud parsers. ## conclusion this study proposed considerations for improving the parsing of wolof, one of the few african languages represented in a ud treebank. in the cases of relative clauses, assigning tags and dependency relations of definites based on their distribution and features provides a better parse than trying to distinguish them as pronoun in certain cases and determiners and demonstratives in others, following patterns from indo-european languages. positing a unified dependency structure for relative clauses also improves parsing. the idea of a copula imported from copular sentences in other languages does not fit the syntax of wolof. rather, classifying part-of-speech tags and labels based on their function in the clause results in a more accurate parse. although the ud framework is lexically oriented, and is more readily translated from lexical functional grammar, insights from the minimalist framework can inform morphological and syntactic annotation. these edited treebank annotations lead to improved parsing in the case of wolof, and are likely to be useful for related african languages. while the wolof ud parser by (dione, 2019) has similar accuracy, the fact that two out-ofthe-box parsers showed improvements with the edited annotations is promising. the final accuracy achieved by this parser is similar to dione's, and suggest that future parsers can attain even greater accuracy if these treebank annotation edits were combined with dione's parser. wolof is a low-resource language with only one treebank, also created by @xcite . 2% is a small but valuable improvement given accuracies of 75%-80% and a smaller treebank relative to langauges like english, french, and russian. the improvements made to parsing compared to the baseline provide guidance for future annotation of african language treebanks, which are not proportionally represented in the ud project.