@inproceedings{sellmer-hellwig-2024-vedic,
    title = "The {V}edic Compound Dataset",
    author = "Sellmer, Sven  and
      Hellwig, Oliver",
    editor = {Bhatia, Archna  and
      Bouma, Gosse  and
      Do{\u{g}}ru{\"o}z, A. Seza  and
      Evang, Kilian  and
      Garcia, Marcos  and
      Giouli, Voula  and
      Han, Lifeng  and
      Nivre, Joakim  and
      Rademaker, Alexandre},
    booktitle = "Proceedings of the Joint Workshop on Multiword Expressions and Universal Dependencies (MWE-UD) @ LREC-COLING 2024",
    month = may,
    year = "2024",
    address = "Torino, Italia",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.mwe-1.8",
    pages = "50--55",
    abstract = "This paper introduces the Vedic Compound Dataset (VCD), the first resource providing annotated compounds from Vedic Sanskrit, a South Asian Indo-European language used from ca. 1500 to 500 BCE. The VCD aims at facilitating the study of language change in early Indo-Iranian and offers comparative material for quantitative cross-linguistic research on compounds. The process of annotating Vedic compounds is complex as they contain five of the six basic types of compounds defined by Scalise {\&} Bisetto (2005), which are, however, not consistently marked in morphosyntax, making their automatic classification a significant challenge. The paper details the process of collecting and preprocessing the relevant data, with a particular focus on the question of how to distinguish exocentric from endocentric usage. It further discusses experiments with a simple ML classifier that uses compound internal syntactic relations, outlines the composition of the dataset, and sketches directions for future research.",
}

This paper introduces the Vedic Compound Dataset (VCD), the first resource providing annotated compounds from Vedic Sanskrit, a South Asian Indo-European language used from ca. 1500 to 500 BCE. The VCD aims at facilitating the study of language change in early Indo-Iranian and offers comparative material for quantitative cross-linguistic research on compounds. The process of annotating Vedic compounds is complex as they contain five of the six basic types of compounds defined by Scalise {\&} Bisetto (2005), which are, however, not consistently marked in morphosyntax, making their automatic classification a significant challenge. The paper details the process of collecting and preprocessing the relevant data, with a particular focus on the question of how to distinguish exocentric from endocentric usage. It further discusses experiments with a simple ML classifier that uses compound internal syntactic relations, outlines the composition of the dataset, and sketches directions for future research.
Sellmer, Sven Hellwig, Oliver
The Vedic Compound Dataset