@inproceedings{bakay-etal-2026-dependency,
    title = "From Dependency to {CCG} to Incremental {CCG}: Approaches to Flexible Word Order in {T}urkish",
    author = {Bakay, {\"O}zge  and
      Y{\i}ld{\i}z, O{\u{g}}uz Kerem  and
      Bhatt, Rajesh  and
      Dillon, Brian  and
      Yildiz, Olcay Taner},
    editor = "Bonial, Claire  and
      Berzak, Yevgeni",
    booktitle = "Proceedings of the 30th Conference on Computational Natural Language Learning",
    month = jul,
    year = "2026",
    address = "San Diego, California, USA",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-acl-workshops/2026.conll-main.36/",
    pages = "601--612",
    ISBN = "979-8-89176-410-1",
    abstract = "Combinatory Categorial Grammar (CCG), a lexicalized formalism known for its flexible constituency, is well-suited for modeling headfinal languages with flexible word order like Turkish. Building on Kuzgun et al. (2023), we first develop a Turkish CCG lexicon by automatically inducing categories from a dependency treebank. By leveraging standard and extended operations tailored to Turkish syntax, our parser achieves a robust coverage of 92.5{\%}. Furthermore, we introduce the first (partially) incremental, left-to-right CCG parser for Turkish, designed to facilitate the immediate integration of words into the evolving representation. Finally, we present an example experiment showing that CCG parsers can model psycholinguistic evidence for extra processing costs associated with arguments in noncanonical positions, via the frequency of order-reversing operations. These findings provide evidence that CCG offers a cognitively plausible framework for modeling real-time processing in languages like Turkish."
}