Jens E. L. Van Gysel

Also published as: Jens E. L. Van Gysel


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Building a Broad Infrastructure for Uniform Meaning Representations
Julia Bonn | Matthew J. Buchholz | Jayeol Chun | Andrew Cowell | William Croft | Lukas Denk | Sijia Ge | Jan Hajič | Kenneth Lai | James H. Martin | Skatje Myers | Alexis Palmer | Martha Palmer | Claire Benet Post | James Pustejovsky | Kristine Stenzel | Haibo Sun | Zdeňka Urešová | Rosa Vallejos | Jens E. L. Van Gysel | Meagan Vigus | Nianwen Xue | Jin Zhao
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

This paper reports the first release of the UMR (Uniform Meaning Representation) data set. UMR is a graph-based meaning representation formalism consisting of a sentence-level graph and a document-level graph. The sentence-level graph represents predicate-argument structures, named entities, word senses, aspectuality of events, as well as person and number information for entities. The document-level graph represents coreferential, temporal, and modal relations that go beyond sentence boundaries. UMR is designed to capture the commonalities and variations across languages and this is done through the use of a common set of abstract concepts, relations, and attributes as well as concrete concepts derived from words from invidual languages. This UMR release includes annotations for six languages (Arapaho, Chinese, English, Kukama, Navajo, Sanapana) that vary greatly in terms of their linguistic properties and resource availability. We also describe on-going efforts to enlarge this data set and extend it to other genres and modalities. We also briefly describe the available infrastructure (UMR annotation guidelines and tools) that others can use to create similar data sets.


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Mapping AMR to UMR: Resources for Adapting Existing Corpora for Cross-Lingual Compatibility
Julia Bonn | Skatje Myers | Jens E. L. Van Gysel | Lukas Denk | Meagan Vigus | Jin Zhao | Andrew Cowell | William Croft | Jan Hajič | James H. Martin | Alexis Palmer | Martha Palmer | James Pustejovsky | Zdenka Urešová | Rosa Vallejos | Nianwen Xue
Proceedings of the 21st International Workshop on Treebanks and Linguistic Theories (TLT, GURT/SyntaxFest 2023)

This paper presents detailed mappings between the structures used in Abstract Meaning Representation (AMR) and those used in Uniform Meaning Representation (UMR). These structures include general semantic roles, rolesets, and concepts that are largely shared between AMR and UMR, but with crucial differences. While UMR annotation of new low-resource languages is ongoing, AMR-annotated corpora already exist for many languages, and these AMR corpora are ripe for conversion to UMR format. Rather than focusing on semantic coverage that is new to UMR (which will likely need to be dealt with manually), this paper serves as a resource (with illustrated mappings) for users looking to understand the fine-grained adjustments that have been made to the representation techniques for semantic categoriespresent in both AMR and UMR.


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Theoretical and Practical Issues in the Semantic Annotation of Four Indigenous Languages
Jens E. L. Van Gysel | Meagan Vigus | Lukas Denk | Andrew Cowell | Rosa Vallejos | Tim O’Gorman | William Croft
Proceedings of the Joint 15th Linguistic Annotation Workshop (LAW) and 3rd Designing Meaning Representations (DMR) Workshop

Computational resources such as semantically annotated corpora can play an important role in enabling speakers of indigenous minority languages to participate in government, education, and other domains of public life in their own language. However, many languages – mainly those with small native speaker populations and without written traditions – have little to no digital support. One hurdle in creating such resources is that for many languages, few speakers would be capable of annotating texts – a task which requires literacy and some linguistic training – and that these experts’ time is typically in high demand for language planning work. This paper assesses whether typologically trained non-speakers of an indigenous language can feasibly perform semantic annotation using Uniform Meaning Representations, thus allowing for the creation of computational materials without putting further strain on community resources.


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Cross-lingual annotation: a road map for low- and no-resource languages
Meagan Vigus | Jens E. L. Van Gysel | Tim O’Gorman | Andrew Cowell | Rosa Vallejos | William Croft
Proceedings of the Second International Workshop on Designing Meaning Representations

This paper presents a “road map” for the annotation of semantic categories in typologically diverse languages, with potentially few linguistic resources, and often no existing computational resources. Past semantic annotation efforts have focused largely on high-resource languages, or relatively low-resource languages with a large number of native speakers. However, there are certain typological traits, namely the synthesis of multiple concepts into a single word, that are more common in languages with a smaller speech community. For example, what is expressed as a sentence in a more analytic language like English, may be expressed as a single word in a more synthetic language like Arapaho. This paper proposes solutions for annotating analytic and synthetic languages in a comparable way based on existing typological research, and introduces a road map for the annotation of languages with a dearth of resources.


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Cross-Linguistic Semantic Annotation: Reconciling the Language-Specific and the Universal
Jens E. L. Van Gysel | Meagan Vigus | Pavlina Kalm | Sook-kyung Lee | Michael Regan | William Croft
Proceedings of the First International Workshop on Designing Meaning Representations

Developers of cross-linguistic semantic annotation schemes face a number of issues not encountered in monolingual annotation. This paper discusses four such issues, related to the establishment of annotation labels, and the treatment of languages with more fine-grained, more coarse-grained, and cross-cutting categories. We propose that a lattice-like architecture of the annotation categories can adequately handle all four issues, and at the same time remain both intuitive for annotators and faithful to typological insights. This position is supported by a brief annotation experiment.

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A Dependency Structure Annotation for Modality
Meagan Vigus | Jens E. L. Van Gysel | William Croft
Proceedings of the First International Workshop on Designing Meaning Representations

This paper presents an annotation scheme for modality that employs a dependency structure. Events and sources (here, conceivers) are represented as nodes and epistemic strength relations characterize the edges. The epistemic strength values are largely based on Saurí and Pustejovsky’s (2009) FactBank, while the dependency structure mirrors Zhang and Xue’s (2018b) approach to temporal relations. Six documents containing 377 events have been annotated by two expert annotators with high levels of agreement.