@inproceedings{dorr-voss-2018-case,
    title = "The Case for Systematically Derived Spatial Language Usage",
    author = "Dorr, Bonnie  and
      Voss, Clare",
    editor = "Kordjamshidi, Parisa  and
      Bhatia, Archna  and
      Pustejovsky, James  and
      Moens, Marie-Francine",
    booktitle = "Proceedings of the First International Workshop on Spatial Language Understanding",
    month = jun,
    year = "2018",
    address = "New Orleans",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/add-emnlp-2024-awards/W18-1408/",
    doi = "10.18653/v1/W18-1408",
    pages = "63--70",
    abstract = "This position paper argues that, while prior work in spatial language understanding for tasks such as robot navigation focuses on mapping natural language into deep conceptual or non-linguistic representations, it is possible to systematically derive regular patterns of spatial language usage from existing lexical-semantic resources. Furthermore, even with access to such resources, effective solutions to many application areas such as robot navigation and narrative generation also require additional knowledge at the syntax-semantics interface to cover the wide range of spatial expressions observed and available to natural language speakers. We ground our insights in, and present our extensions to, an existing lexico-semantic resource, covering 500 semantic classes of verbs, of which 219 fall within a spatial subset. We demonstrate that these extensions enable systematic derivation of regular patterns of spatial language without requiring manual annotation."
}