@inproceedings{mikhael-2025-computational,
    title = "A Computational {C}x{G} Aided search for `come to' constructions in a corpus of {A}frican {A}merican Novels from 1920 to 1930",
    author = "Mikhael, Kamal Abou",
    editor = "Bonial, Claire  and
      Torgbi, Melissa  and
      Weissweiler, Leonie  and
      Blodgett, Austin  and
      Beuls, Katrien  and
      Van Eecke, Paul  and
      Tayyar Madabushi, Harish",
    booktitle = "Proceedings of the Second International Workshop on Construction Grammars and NLP",
    month = sep,
    year = "2025",
    address = {D{\"u}sseldorf, Germany},
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/2025.cxgsnlp-1.21/",
    pages = "202--207",
    ISBN = "979-8-89176-318-0",
    abstract = "This paper presents a pilot study of metaphors of motion in African American literary language (AALL) in two sub-corpora of novels published in 1920-1925 and 1926-1930. It assesses the effectiveness of Dunn{'}s (2024) unsupervised learning approach to computational construction grammar (c2xg) as a basis for searching for constructional metaphors, a purpose beyond its original design as a grammar-learning tool. This method is chosen for its statistical orientation and employed without pre-trained models to minimize bias towards standard language; its output is also used to choose a target search term. Focusing on the verbal phrase `come to', the study analyzes argument-structure constructions that instantiate conceptual metaphors, most prominently experiencer-as-theme (e.g., `he came to know') and experiencer-as-goal (e.g., `thoughts came to her'). The evaluation compares c2xg coverage against a manually annotated set of metaphors and examines the uniformity of metaphor types extracted. Results show that c2xg captures 52{\%} and 63{\%} of metaphoric constructions in the two sub-corpora, with variation in coverage and uniformity depending on the ambiguity of the construct. The study underscores the value of combining computational and manual analysis to obtain outcomes that are both informative and ethically aware when studying marginalized varieties of English."
}