@inproceedings{roesiger-2018-rule,
    title = "Rule- and Learning-based Methods for Bridging Resolution in the {ARRAU} Corpus",
    author = "Roesiger, Ina",
    editor = "Poesio, Massimo  and
      Ng, Vincent  and
      Ogrodniczuk, Maciej",
    booktitle = "Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference",
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W18-0703/",
    doi = "10.18653/v1/W18-0703",
    pages = "23--33",
    abstract = "We present two systems for bridging resolution, which we submitted to the CRAC shared task on bridging anaphora resolution in the ARRAU corpus (track 2): a rule-based approach following Hou et al. 2014 and a learning-based approach. The re-implementation of Hou et al. 2014 achieves very poor performance when being applied to ARRAU. We found that the reasons for this lie in the different bridging annotations: whereas the rule-based system suggests many referential bridging pairs, ARRAU contains mostly lexical bridging. We describe the differences between these two types of bridging and adapt the rule-based approach to be able to handle lexical bridging. The modified rule-based approach achieves reasonable performance on all (sub)-tasks and outperforms a simple learning-based approach."
}