Spanish Abstract Meaning Representation: Annotation of a General Corpus. Wein, S., Donatelli, L., Ricker, E., Engstrom, C., Nelson, A., Harter, L., & Schneider, N. In Northern European Journal of Language Technology, Volume 8, Copenhagen, Denmark, 2022. Northern European Association of Language Technology. Paper doi abstract bibtex 2 downloads Abstract Meaning Representation (AMR), originally designed for English, has been adapted to a number of languages to facilitate cross-lingual semantic representation and analysis. We build on previous work and present the first sizable, general annotation project for Spanish AMR. We release a detailed set of annotation guidelines and a corpus of 486 gold-annotated sentences spanning multiple genres from an existing, cross-lingual AMR corpus. Our work constitutes the second largest non-English gold AMR corpus to date. Fine-tuning an AMR to-Spanish generation model with our annotations results in a BERTScore improvement of 8.8%, demonstrating initial utility of our work.
@inproceedings{wein-2022-spanish,
title = "{S}panish {A}bstract {M}eaning {R}epresentation: Annotation of a General Corpus",
author = "Wein, Shira and
Donatelli, Lucia and
Ricker, Ethan and
Engstrom, Calvin and
Nelson, Alex and
Harter, Leonie and
Schneider, Nathan",
booktitle = "Northern European Journal of Language Technology, Volume 8",
year = "2022",
address = "Copenhagen, Denmark",
publisher = "Northern European Association of Language Technology",
url = "https://aclanthology.org/2022.nejlt-1.6",
doi = "https://doi.org/10.3384/nejlt.2000-1533.2022.4462",
abstract = "Abstract Meaning Representation (AMR), originally designed for English, has been adapted to a number of languages to facilitate cross-lingual semantic representation and analysis. We build on previous work and present the first sizable, general annotation project for Spanish AMR. We release a detailed set of annotation guidelines and a corpus of 486 gold-annotated sentences spanning multiple genres from an existing, cross-lingual AMR corpus. Our work constitutes the second largest non-English gold AMR corpus to date. Fine-tuning an AMR to-Spanish generation model with our annotations results in a BERTScore improvement of 8.8{\%}, demonstrating initial utility of our work.",
}
Downloads: 2
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