Morphological Reinflection with Multiple Arguments: An Extended Annotation schema and a G eorgian Case Study (2022)

Abstract: In recent years, a flurry of morphological datasets had emerged, most notably UniMorph, aa multi-lingual repository of inflection tables. However, the flat structure of the current morphological annotation makes the treatment of some languages quirky, if not impossible, specifically in cases of polypersonal agreement. In this paper we propose a general solution for such cases and expand the UniMorph annotation schema to naturally address this phenomenon, in which verbs agree with multiple arguments using true affixes. We apply this extended schema to one such language, Georgian, and provide a human-verified, accurate and balanced morphological dataset for Georgian verbs. The dataset has 4 times more tables and 6 times more verb forms compared to the existing UniMorph dataset, covering all possible variants of argument marking, demonstrating the adequacy of our proposed scheme. Experiments on a reinflection task show that generalization is easy when the data is split at the form level, but extremely hard when splitting along lemma lines. Expanding the other languages in UniMorph according to this schema is expected to improve both the coverage, consistency and interpretability of this benchmark.

## introduction in recent years, morphological (re)inflection tasks have gained a lot of attention in nlp. 1 subsequently, several multi-lingual morphological datasets have emerged to allow for the supervised training of morphological models, most notably unimorph @xcite , that organizes words into inflectional tables, annotating each inflected word-form with its respective feature-set. while western languages are widely represented in unimorph, many morphologically rich languages @xcite exhibit rich and diverse inflection patterns that make them less compatible with the flat feature-sets in the uni-morph schema. concretely, in some cases it is completely impossible to annotate parts of the inflectional paradigm with a flat bundle, as is the case with case stacking, and in other cases, such as polypersonal agreement, the annotation solutions provided are unnatural, non-transparent, and are barely used in practice. as a result, languages exhibiting such phenomena are under-represented in unimorph, and when they are, the inflection tables for these languages are often incomplete. in this paper we propose a general solution for annotating such structures, thus extending the unimorph annotation schema to fully cover a wider range of morphologically-complex argumentmarking phenomena. following @xcite , we propose a so-called layered annotation of features, where the inflectional features take the form of a hierarchical structure, in the spirit of formal linguistic frameworks as that of @xcite ; @xcite ; @xcite ; @xcite . we organize the features of multiple arguments in a hierarchical structure, rather than the current flat structure that accommodates only subject concords. this schema shift allows for an adequate annotation of polypersonal agreement and of possessed nominals, where a word has multiple number and gender features, as well as forms with case stacking, where a word has multiple cases. we apply the suggested solution to georgian, an agglutinative language with a convoluted verbal system, that indicates both subjects and objects with true affixes (rather than clitics that are omittable from the inflection tables). we create a new human-verified dataset for georgian, that covers most of the grammatical phenomena in georgian verbs, and includes 118 lemmas, adding up to about 21k verb forms, compared with the 47 lemmas and 3.3k verb forms, some of which are erroneous, currently available in the georgian unimorph. we use the new dataset to train a standard morphological reinflection model @xcite and show that training on the georgian inflections currently available in unimorph is not sufficient for generalizing to the more inclusive set of inflections that are allowed by the new scheme. we conclude that our annotation approach provides a more complete representation of linguistic behaviors, and that our proposed georgian dataset provides a much better depiction of the morphological phenomena that exist in the data and the computational challenge reflected therein. we therefore call to apply layered annotation to all currently existing morphological data in uni-morph, to more consistently and transparently capture the linguistic reality and morphological complexity reflected in the worlds languages. ## the problem: multiple arguments models of morphological reinfection are trained to generate forms within a lemma l, given another form and the features of source i and target j forms: for example, for the russian lemma лететь: reinflecting from (prs;1;sg,лечу) to (imp;2;sg,лети) will be represented as: ⟨prs;1;sg, лечу⟩, ⟨imp;2;sg, ___⟩ → лети standardly, the data for training morphological models (e.g., @xcite is taken from unimorph @xcite , a multilingual morphological dataset in which words are grouped by lemma into inflection tables, each word is tagged with an unordered set of morphological features. the features list is shared across languages. the inflection tables are meant to be exhaustive, i.e., covering all possible forms of a lemma, regardless of usability. although the features were designed to apply cross-lingually, some blind-spots exist. most relevant to our work is the assumption that every feature set includes at most one pronominal feature bundle (i.e., person-gender-number). however, this assumption does not apply to verbs with object concords, as exhibited in georgian (see georgian: gagišvebt 'we will let you go' (subj-1pl, obj-2sg) b. turkish: kedisisin 'you are his cat' (noun-sg, subj-2sg, poss-3sg) c. swahili: ninakupenda 'i love you' (subj-1sg, obj-2sg) d. hebrew: emdata 'her position' (noun-sg, poss-3sg-fem) the solution proposed in unimorph to annotating these phenomena is via concatenating several properties into a single string, lacking any internal structure; e.g., argac2s indicates a form with a 2nd person singular accusative argument (sylak-glassman, 2016). however, there are at least two shortcomings to this solution. first, it is not sufficiently transparent. argac2s is an opaque string, that does not decompose into the known features licensed by the unimorph features list (i.e., acc, 2, sg). secondly, and possibly due to this lack of transparency, this annotation hack is hardly ever used in practice. hence, from all examples in (1), only the hebrew form is included in unimorph, and tagged as n;sg;fem;pss3s with multiple possessor features merged into the flat string pss3s. the crux of the matter is that in the current annotation schema, complex features assigned to additional arguments are treated as a single nondecomposable feature, that lack any internal structure, unlike the features of the main (so-called 'internal') argument, that are individually spelled out. we argue that the lack of transparency and usability are due to the misrepresentation of the inherently hierarchical and compositional structure of the features in such forms. we suggest to explicitly annotate these forms with features that are all explicitly composed of the same primitive features. all in all, the lack of a sufficiently expressive annotation standard leads to a data distribution that is skewed, unrealistically simple, and, when languagespecific annotation solutions are painfully needed, they suffer from inconsistencies and ad-hoc decisions. for these reasons, we set out to extend the unimorph annotation schema to accommodate all such cases and to enable a proper coverage of languages, such as georgian and many others. ## the proposed schema we propose to extend the unimorph annotation schema to cover multiple pronominal featurebundles in the same word-form, via a layering approach, originally proposed for morphological systems by @xcite . anderson suggests to arrange the morphosyntactic representation (msr) of words in a hierarchy (dubbed layers) of features, in the sense that every element of the unordered set of features can be composed of another unordered set of features. that is, a general feature annotation looks as in (2a). a specific transitive verb annotation could be as depicted in ( 2b this hierarchical feature structure is reminiscent of unification grammars or attribute-value grammars @xcite ) that are extensively used in syntactic theories such as gpsg, hpsg, and resemble the f-structures in lfg @xcite @xcite . here we employ these structures to organize the features of morphologically-marked arguments hierarchically, so an argument is characterized by a feature composite of all features pertaining to that argument. that is, each argument's featurebundle os specifically marked with the argument it belongs to, and is decomposed into the primitive features licensed by the unimorph scheme. it also homogeneously annotates the different kinds of arguments, in contrast with the current schema where the subject features are assigned to the verb directly. thus, the english form thinks previously annotated as v;prs;3;sg will be annotated as v;prs;nom(3;sg). in languages that mark multiple arguments, different kinds of arguments can be marked with their feature-bundles without conflicts. the proposed schema thus facilitates the annotation of the poorly-treated or untreated phenomena as illustrated in (1). these are, respectively: the resemblance of our proposed schema to ideas in other fields of theoretical linguistics, most prominently to the f-structure in lfg @xcite and to the nested attribute-value matrices in hpsg @xcite , points to a natural interface with further syntactic and semantic annotations downstream. ## a case study from georgian linguistic background georgian is an agglutinative language with a verbal system that makes a vast use of affixes to convey a wide array of meanings, both inflectional and derivational (see the characteristic most essential to this work is that georgian verbs always agree on person and number with the direct and indirect objects, on top of the subject-verb agreement. the georgian data in unimorph follows the convention of including objects only in third person singular -thus failing to provide a comprehensive coverage of the wordforms that can be attested in the language. additional issues with the current morphological data in unimorph for georgian verbs are: sparsity, as it includes only 47 inflection tables; lack of diversity, as all table are from the transitive class; and lack of accuracy, as the data was produced automatically without verification by native speakers. ## experiments to assess the usability of our dataset, we trained a standard reinflection model, the character-level lstm of @xcite , on our data. 5 we sampled from our data 2 datasets for training morphological reinflection models, containing train, validation and test sets in sizes 8k, 1k and 1k examples, respectively. following @xcite , one dataset employed an easier formsplit, i.e., no forms appear in both train and test, 6 and the other with the more challenging lemmasplit, where lemmas from train, dev and test are disjoint. to assess the generalization capacity we varied the sources of both the train and test sets. 7 we report 2 evaluation metrics: accuracy over exact matches, and average edit distance from gold. ## conclusion this paper proposes a transition of the unimorph annotation standard to a layered hierarchical annotation of features. this revised schema caters for complex marking phenomena including multiple pronominal agreement. we apply it to georgian, and construct a corresponding new dataset that is large, balanced, complete with respect to grammatical phenomena in the georgian verb system and verified by native-speakers. our experiments with a standard reinflection model on the old and new georgian datasets shows that the old unimorph dataset does not generalize well to the new testset, due to its partial coverage. this work is intended to encourage the community to extend the annotation of different languages to include phenomena such as polypersonal agreement and others that can be dealt with using a hierarchical annotation, ultimately leading to more complete and consistent benchmarks for studying non-trivial and less-explored areas of computational morphology.