The paper examines the grammatical behavior of the negative element used to negate predicates in non-verbal clauses in three Turkic languages: Azerbaijani, Kyrgyz, and Turkish. We focus on its interaction with verbal copulas, subject agreement, and the distribution of agreement suffixes, as well as its position within the predicate phrase. The study draws on both previously described corpus data and newly collected examples. Across all three languages, agreement features are realised on the negative element only in the absence of an overt copula. The agreement morphology involved is identical to that found with nominal, adjectival, and adverbial predicates. In all the languages examined, the negative element remains within the predicate phrase; thus, its position is syntactically constrained. At the same time, we observe differences among the languages in the degree to which the position of the negator is fixed within the predicate. In Turkish and Azerbaijani, regardless of which element of the nominal predicate it negates, the negator invariably follows the predicate. In Kyrgyz, by contrast, it consistently appears immediately after the element it negates within the predicate. These patterns suggest that the negative element behaves syntactically as a phrasal operator associated with non-verbal predicates. For annotation purposes, we therefore propose analysing the negative element as a negation modifier, assigning it the POS tag ADV and the dependency relation advmod:neg.

This paper presents the first ever morphological transducer for the Limbu language, also known by its endonym Yakthung Pan, an endangered Sino-Tibetan language primarily spoken in the area known as Limbuwan/Koshi Province in Eastern Nepal, with a minority population in the Sikkim state of India, where Limbu enjoys official status. Using a corpus of Limbu text produced by field interviews (Michailovsky, 1977), and a translation of the Holy Bible into the Limbu language, the paper presents various elements of the morphology of the language, how they were implemented into the transducer, and an evaluation of the transducer against identified corpora and a gold standard. With a relatively small lexicon, the transducer was found to have reasonable coverage, with high precision but low recall. The paper discusses future expansion through further involvement with the community, which can help in the maintenance and revitalisation of the endangered language.

We present a Kyrgyz language seed dataset as part of our contribution to the WMT25 Open Language Data Initiative (OLDI) shared task. This paper details the process of collecting and curating English–Kyrgyz translations, highlighting the main challenges encountered in translating into a morphologically rich, low-resource language. We demonstrate the quality of the dataset through fine-tuning experiments, showing consistent improvements in machine translation performance across multiple models. Comparisons with bilingual and MNMT Kyrgyz-English baselines reveal that, for some models, our dataset enables performance surpassing pretrained baselines in both English–Kyrgyz and Kyrgyz–English translation directions. These results validate the dataset’s utility and suggest that it can serve as a valuable resource for the Kyrgyz MT community and other related low-resource languages.

This paper presents work towards a morphological transducer for Hän, a Dene language spoken in Alaska and the Yukon Territory. We present the implementation of several complex morphological features of Dene languages into a morphological transducer, an evaluation of the transducer on corpus data, and a discussion of the future uses of such a transducer towards Hän revitalization efforts.

As part of our efforts to develop unified Universal Dependencies (UD) guidelines for Turkic languages, we evaluate multiple approaches to a difficult morphosyntactic phenomenon, pronominal locative expressions formed by a suffix -ki. These forms result in multiple syntactic words, with potentially conflicting morphological features, and participating in different dependency relations. We describe multiple approaches to the problem in current (and upcoming) Turkic UD treebanks, and show that none of them offers a solution that satisfies a number of constraints we consider (including constraints imposed by UD guidelines). This calls for a compromise with the ‘least damage’ that should be adopted by most, if not all, Turkic treebanks. Our discussion of the phenomenon and various annotation approaches may also help treebanking efforts for other languages or language families with similar constructions.

The Universal Morphology (UniMorph) project is a collaborative effort providing broad-coverage instantiated normalized morphological inflection tables for hundreds of diverse world languages. The project comprises two major thrusts: a language-independent feature schema for rich morphological annotation, and a type-level resource of annotated data in diverse languages realizing that schema. This paper presents the expansions and improvements on several fronts that were made in the last couple of years (since McCarthy et al. (2020)). Collaborative efforts by numerous linguists have added 66 new languages, including 24 endangered languages. We have implemented several improvements to the extraction pipeline to tackle some issues, e.g., missing gender and macrons information. We have amended the schema to use a hierarchical structure that is needed for morphological phenomena like multiple-argument agreement and case stacking, while adding some missing morphological features to make the schema more inclusive. In light of the last UniMorph release, we also augmented the database with morpheme segmentation for 16 languages. Lastly, this new release makes a push towards inclusion of derivational morphology in UniMorph by enriching the data and annotation schema with instances representing derivational processes from MorphyNet.

We present, to our knowledge, the first ever published morphological analyser and generator for Sakha, a marginalised language of Siberia. The transducer, developed using HFST, has coverage of solidly above 90%, and high precision. In the development of the analyser, we have expanded linguistic knowledge about Sakha, and developed strategies for complex grammatical patterns. The transducer is already being used in downstream tasks, including computer assisted language learning applications for linguistic maintenance and computational linguistic shared tasks.

We present a free/open-source morphological transducer for Western Armenian, an endangered and low-resource Indo-European language. The transducer has virtually complete coverage of the language’s inflectional morphology. We built the lexicon by scraping online dictionaries. As of submission, the transducer has a lexicon of 75K words. It has over 90% naive coverage on different Western Armenian corpora, and high precision.

This year’s iteration of the SIGMORPHON Shared Task on morphological reinflection focuses on typological diversity and cross-lingual variation of morphosyntactic features. In terms of the task, we enrich UniMorph with new data for 32 languages from 13 language families, with most of them being under-resourced: Kunwinjku, Classical Syriac, Arabic (Modern Standard, Egyptian, Gulf), Hebrew, Amharic, Aymara, Magahi, Braj, Kurdish (Central, Northern, Southern), Polish, Karelian, Livvi, Ludic, Veps, Võro, Evenki, Xibe, Tuvan, Sakha, Turkish, Indonesian, Kodi, Seneca, Asháninka, Yanesha, Chukchi, Itelmen, Eibela. We evaluate six systems on the new data and conduct an extensive error analysis of the systems’ predictions. Transformer-based models generally demonstrate superior performance on the majority of languages, achieving >90% accuracy on 65% of them. The languages on which systems yielded low accuracy are mainly under-resourced, with a limited amount of data. Most errors made by the systems are due to allomorphy, honorificity, and form variation. In addition, we observe that systems especially struggle to inflect multiword lemmas. The systems also produce misspelled forms or end up in repetitive loops (e.g., RNN-based models). Finally, we report a large drop in systems’ performance on previously unseen lemmas.

This paper presents work towards a morphological transducer and orthography converter for Dizhsa, or San Lucas Quiaviní Zapotec, an endangered Western Tlacolula Valley Zapotec language. The implementation of various aspects of the language’s morphology is presented, as well as the transducer’s ability to perform analysis in two orthographies and convert between them. Potential uses of the transducer for language maintenance and issues of licensing are also discussed. Evaluation of the transducer shows that it is fairly robust although incomplete, and evaluation of orthographic conversion shows that this method is strongly affected by the coverage of the transducer.

This paper presents a shallow-transfer machine translation (MT) system for translating from Kazakh to Turkish. Background on the differences between the languages is presented, followed by how the system was designed to handle some of these differences. The system is based on the Apertium free/open-source machine translation platform. The structure of the system and how it works is described, along with an evaluation against two competing systems. Linguistic components were developed, including a Kazakh-Turkish bilingual dictionary, Constraint Grammar disambiguation rules, lexical selection rules, and structural transfer rules. With many known issues yet to be addressed, our RBMT system has reached performance comparable to publicly-available corpus-based MT systems between the languages.

Syllabification does not seem to improve word-level RNN language modeling quality when compared to character-based segmentation. However, our best syllable-aware language model, achieving performance comparable to the competitive character-aware model, has 18%-33% fewer parameters and is trained 1.2-2.2 times faster.

~This paper describes the development of free/open-source finite-state morphological transducers for Tuvan, a Turkic language spoken in and around the Tuvan Republic in Russia. The finite-state toolkit used for the work is the Helsinki Finite-State Toolkit (HFST), we use the lexc formalism for modelling the morphotactics and twol formalism for modelling morphophonological alternations. We present a novel description of the morphological combinatorics of pseudo-derivational morphemes in Tuvan. An evaluation is presented which shows that the transducer has a reasonable coverage―around 93%―on freely-available corpora of the languages, and high precision―over 99%―on a manually verified test set.

This paper describes the development of free/open-source finite-state morphological transducers for three Turkic languages―Kazakh, Tatar, and Kumyk―representing one language from each of the three sub-branches of the Kypchak branch of Turkic. The finite-state toolkit used for the work is the Helsinki Finite-State Toolkit (HFST). This paper describes how the development of a transducer for each subsequent closely-related language took less development time. An evaluation is presented which shows that the transducers all have a reasonable coverage―around 90%―on freely available corpora of the languages, and high precision over a manually verified test set.

This paper describes the development of a free/open-source finite-state morphological transducer for Kyrgyz. The transducer has been developed for morphological generation for use within a prototype Turkish→Kyrgyz machine translation system, but has also been extensively tested for analysis. The finite-state toolkit used for the work was the Helsinki Finite-State Toolkit (HFST). The paper describes some issues in Kyrgyz morphology, the development of the tool, some linguistic issues encountered and how they were dealt with, and which issues are left to resolve. An evaluation is presented which shows that the transducer has medium-level coverage, between 82% and 87% on two freely available corpora of Kyrgyz, and high precision and recall over a manually verified test set.