Fitting a Square Peg into a Round Hole: Creating a U ni M orph dataset of Kanien’kéha Verbs (2024)

Abstract: This paper describes efforts to annotate a dataset of verbs in the Iroquoian language Kanien’kéha (a.k.a. Mohawk) using the UniMorph schema (Batsuren et al. 2022a). It is based on the output of a symbolic model - a hand-built verb conjugator. Morphological constituents of each verb are automatically annotated with UniMorph tags. Overall the process was smooth but some central features of the language did not fall neatly into the schema which resulted in a large number of custom tags and a somewhat ad hoc mapping process. We think the same difficulties are likely to arise for other Iroquoian languages and perhaps other North American language families. This paper describes our decision making process with respect to Kanien’kéha and reports preliminary results of morphological induction experiments using the dataset.

## introduction it is generally believed that building language technology for morphologically rich languages benefits from knowing about morphology. other things held constant, providing morphological information as a part of an nlp pipeline is likely to help, e.g. @xcite @xcite . while there is no clear-cut definition of what makes a language morphologically rich, usually it refers to languages where words are composed of many parts. it certainly applies to most language families in north america (e.g. algonquian, iroquoian, eskimo-aleut, etc.) computational models of morphology are important also because mastering morphology is crucial when learning a morphologically rich language. methods, techniques and aids that help students master morphology are helpful in speeding up the learning process @xcite . the work described in this paper is a small step in this direction for kanien'kéha, a.k.a. the mo-hawk language. it started as a collaboration between the national research council canada ( further nrc) and a kanien'kéha immersion school for adults, onkwawénna kentyóhkwa. the teachers at the school noticed that students in the immersion classes struggled most with mastering verbal morphology and often created hand-made 'verb conjugators' as study aids. the role of the nrc was to help build an interactive verb conjugator that was aligned with the school's curriculum. to the best of our knowledge this was the first computational model of a subset of kanien'kéha grammar. however, we were unable to use any data driven methods because of the extreme paucity of textual data in kanien'kéha. one of the side effects of creating a symbolic language model was the creation of a large dataset of verbs (1,419k conjugations), complete with inflectional information and morphological segmentation. we have mapped this dataset into the uni-morph framework. the motivation for this paper is two-fold. firstly, the paper serves as a reference document for a new dataset for morphological induction in kanien'kéha. the paper documents the dataset itself as well as the arbitrary decisions made during the labelling process. the second goal of this paper is to illustrate that such references are necessary when creating datasets for low-resource languages, especially less documented ones. we demonstrate several paradigms in the language that cannot be adequately described using the unimorph framework without defining a large number of custom labels (e.g. pronominal system, aspect system, transitivity etc.). in some cases, existing unimorph dimensions and features seem acceptable but upon closer inspection applying them would be misleading. these remarks are not meant as a criticism of unimorph, but rather as suggestions for future updates of the schema. this is especially so since the same properties are common not only to all iroquoian languages, but also to other language families in north america (e.g. algonquian). the main contribution of this work is the dataset foot_0 . the second contribution is preliminary results of morphological inflection experiments using this dataset. to the best of our knowledge, this is the first data-driven or corpus-based model of kanien'kéha. this paper is structured as follows. section 2 places the work into existing research context. section 3 provides a brief overview of the language. section 4 gives an overview of unimorph. section 5 describes the initial data used for annotation. section 6 is the main description of the new dataset and the decisions made. section 7 briefly describes experiments and reports results. sections 8 and 9 contain discussion and describe limitations of this work. ## kanien'kéha and iroquoian languages iroquoian languages are a group of approximately 17 historically documented languages situated in southeastern canada (ontario and quebec) and northeastern us (new york state, but also in north carolina and oklahoma). all spoken iroquoian languages that still have first-language speakers (further l1) (cherokee, seneca, cayuga, onondaga, oneida and kanien'kéha) are endangered. several others are either undergoing revitalization within communities or are considered sleeping languages. the majority of l1 speakers are older than 75. however, in several communities a small number of new l1 speakers are being raised by parents who are l2 speakers. linguistically, iroquoian languages can be divided into southern iroquoian and northern iroquoian branches. there is only one southern iroquoian language -cherokee. the northern branch of the iroquoian language family contains all original five nations languages of the haudenosaunee confederacy. many other iroquoian languages are no longer spoken, with scant word lists available (e.g. wyandot, petun, meherrin, neutral, wenro and erie to name just a few) @xcite . despite the current harsh linguistic reality, due to the effects of continued colonization and governments' efforts to linguistically and culturally destroy them, the language communities are very focused and interested in strengthening and reestablishing their ancestral languages. many im-pressive and successful efforts are ongoing and evolving to fit their contemporary needs. the authors of the paper are only familiar with some of the communities and regret inevitable omissions. however, examples of thriving language schools are seen at twatati adult oneida immersion program for oneida foot_1 , yawenda project for wendat foot_2 and onkwawenna kentyohkwa foot_3 and kanien'kehá:ka onkwawén:na raotitióhkwa language and cultural center for kanien'kéha ratiwennahní:rats adult language immersion program foot_4 . all iroquoian languages are morphologically complex, with verbs being particularly elaborate. verbs are composed of several parts, both prefixes and suffixes, as well as noun incorporation. due to the languages' rich morphology, the linguistic practice of creating new words is deeply cultural, therefore restricting borrowing from other languages. generally speaking, single-token verbs in an iroquoian language correspond to simple clauses in english (however simpler verbs are possible too): fut-@xmath0; he'll fix my car' (kanien'kéha) (2) yusayenhohayapákhup y-usa-ye-nhoh-a-yapak-hu-p there-again.did-she-door-link-hit-many-punc transl-rep.fact-fi.a-door-jr-hit--distr-punc 'she knocked on the door again' (oneida) example 1 and example 2 are two unremarkable kanien'kéha and oneida verbs @xcite ) that correspond to simple clauses in english. since this work only focuses on verbal morphology, we will only discuss that part of speech from here on in. a minimal verb structure consists of a pronominal prefix, a verb stem and an aspectual suffix, which can be null. a verb stem can be simple or have a noun incorporated, as in example 1. additionally, a verb can also have pre-pronominal prefixes and the verb stem can include one or more prefixes or suffixes; these convey inflectional and derivational meanings. ## unimorph the unimorph project @xcite has two main parts: an annotation schema and an extensive collection of inflection tables for 182 languages, several dozens of them for endangered languages of the world. it also contains several datasets for morpheme segmentation and for derivational morphology. the original goal of the project was to develop a language-independent schema that could adequately describe inflectional morphological breakdowns of words in any language. currently in its 4.0 version, the unimorph schema has been extended and improved but its skeleton remains unchanged. the unimorph schema contains 25 dimensions listed in stem inflected unimorph lang. form tags mercify mercifies v;prs;3;sg en mercify mercifying v;v.ptcp;prs en abalienare abalienò v;ind;pst;3;sg;pfv it abbacare abbacai v;ind;pst;1;sg;pfv it for the dimension animacy are animate, human, inanimate, non-human. when default features are insufficient the annotators can also create language specific tags. using the unimorph schema is not the only option. we could have devised our own set of tags as in @xcite . we decided to opt for standardization possibly at the expense of specificity. this decision is due to the practical nature of our objectives. as the overarching goal is improving language technology for kanien'kéha, choosing a widely used standard (unimorph) seems more practical and more accessible for future users than devising our own. ## the dataset kawennón:nis is an interactive verb conjugator for kanien'kéha available online or locally. currently two version of the software exist: one for the ohswé:ken dialect (ohswekèn:'a) and another for the kahnawà:ke dialect (kahnawa'kéha). this paper describes the dataset for kahnawa'kéha. this tool was designed as a teaching aid for students of immersion programs of kanien'kéha and closely follows the curriculum. it allows the user to select one or more verb stems, one or more sets of pronominal prefixes and one or more tenses, and then outputs the corresponding conjugations. the tool has been designed in close collaboration with onkwawénna kentyóhkwaimmersion school. following a user study and several consultations with teachers and students, a local artist was employed to design a culturally relevant interface. the tool contains 662 verb stems and more are being added. it allows the user to choose one or more of the 12 available tense/aspect options, as well as apply negation and repetition. it does not contain derivational morphology, although we hope to add contained subsets in the future. the complete output of the tool corresponds to inflectional tables for the 662 verbs within the modeled paradigms -1,418,939 inflected forms. however because the dataset contains inflectional tables as opposed to intelligently created samples, there is a lot of redundancy (the size grows exponentially with the number of paradigms modeled). stress in kanien'kéha is quite complex and is a major source of irregularities. we make available both the stressed and the unstressed versions on the dataset. extensive work has been done to ensure the quality of the dataset but as any computational model, it contains errors. 244 of the 662 inflection table files have been manually checked by an advanced l2 speaker who is an experienced teacher and linguist. as was mentioned in section 3 there are very few l1 speakers of kanien'kéha; what is even more important is that their time is better spent than checking conjugation tables. we realize that thorough evaluation is a weakness of this work but it is an unfortunate consequence of the capacity bottleneck. ## unimorph and kanien'kéha our dataset contains only active verbs (as opposed to stative) and captures only foundational morphological paradigms. therefore, only verb-related parts of the unimorph schema are relevant to us. in this section we describe our efforts to align the properties of the language with the unimorph schema. the process of mapping was not straightforward and arguably alternative choices could have been made. yet, despite some difficulties we were able to automatically label our existing dataset, take advantage of the existing systems and train a model for morphological inflection in kanien'kéha. preliminary results are available in section 7. ## experiments for our experiments we apply the neural characterlevel transformer @xcite that is used as a competitive baseline in @xcite . we use the highresource setting and the only parameter we change from default settings is the batch size, which we set to 1000 foot_5 . the final version of the dataset contains 1,418,893 inflected verb forms. we split them into training, development and test sets in a 0.7 : 0.1 : 0.2 ratio. the splits are done at the level of individual verbs: the same verb does not appear in more than one split (and consequently none of the conjugated examples are overlapping either). the exception to this statement are verbs that can behave as both transitive and intransitive ones: in these cases while the stem is the same, the morphological preferences are different. because of this we do not control that such verbs do not appear in training/development sets and test sets simultaneously. the stress system is a major source of exceptions. in addition to placement of stress, it also determines variations in length and tone and whether some characters are omitted. because of these challenges we create a second dataset without stress. to produce the dataset, we use the output of the symbolic model before stress rules are applied. the results are shown in preliminary error analysis suggests that indeed stress-related errors are common. however the biggest source of mistakes seems to be changes in verb stems related to aspect (habitual, punctual, stative and imperatives). this is supported by opinions of the speakers that aspectual endings are largely lexicalized with many exceptions from general loose rules. in the symbolic system used as the original source of data, four forms are given as input for each verb stem. the neural system learned how to generalize those forms, albeit imperfectly. we hope to address these shortcomings in future work. since stress in kanien'kéha is determined from the end of the word, in right-to-left fashion, we expect that applying a right-to-left system such as that of @xcite may help. also, we hope that learning generic rules about orthography in kanien'kéha from an existing corpus may improve both stress and aspectual-class related errors. ## conclusions we have described the first dataset for morphological induction for the iroquoian language kanien'kéha. due to community preferences, the dataset is not publicly available by default but is available upon request for research and educational purposes. while describing the dataset, we have demonstrated that the process of mapping ready morphologically segmented data into unimorph is neither trivial nor always straight-forward. some of the problematic categories, common to other iroquoian languages, are tense, aspect, voice and mood. we have also reported first results of morphological induction experiments on this dataset. in the future, we have practical and research directions to consider. we hope to use the results of experiments to speed up the circular process of improving the symbolic model, extending this dataset and hopefully eventually exceeding the precision of the symbolic model. we also are exploring ways to improve performance on this dataset. one such avenue was mentioned in section 7: using a learning model that considers both left-to-right and right-to-left input directions. we also would like to look into creating similar resources for related languages for which symbolic models already exist, e.g. oneida @xcite and cherokee foot_6 .