Fabian Simonjetz


Reference to Discourse Topics: Introducing “Global” Shell Nouns
Fabian Simonjetz
Proceedings of the Third Workshop on Computational Models of Reference, Anaphora and Coreference

Shell nouns (SNs) are abstract nouns like “fact”, “issue”, and “decision”, which are capable of refer- ring to non-nominal antecedents, much like anaphoric pronouns. As an extension of classical anaphora resolution, the automatic detection of SNs alongside their respective antecedents has received a growing research interest in recent years but proved to be a challenging task. This paper critically examines the assumption prevalent in previous research that SNs are typically accompanied by a specific antecedent, arguing that SNs like “issue” and “decision” are frequently used to refer, not to specific antecedents, but to global discourse topics, in which case they are out of reach of previously proposed resolution strategies that are tailored to SNs with explicit antecedents. The contribution of this work is three-fold. First, the notion of global SNs is defined; second, their qualitative and quantitative impact on previous SN research is investigated; and third, implications for previous and future approaches to SN resolution are discussed.


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Anaphora Resolution with the ARRAU Corpus
Massimo Poesio | Yulia Grishina | Varada Kolhatkar | Nafise Moosavi | Ina Roesiger | Adam Roussel | Fabian Simonjetz | Alexandra Uma | Olga Uryupina | Juntao Yu | Heike Zinsmeister
Proceedings of the First Workshop on Computational Models of Reference, Anaphora and Coreference

The ARRAU corpus is an anaphorically annotated corpus of English providing rich linguistic information about anaphora resolution. The most distinctive feature of the corpus is the annotation of a wide range of anaphoric relations, including bridging references and discourse deixis in addition to identity (coreference). Other distinctive features include treating all NPs as markables, including non-referring NPs; and the annotation of a variety of morphosyntactic and semantic mention and entity attributes, including the genericity status of the entities referred to by markables. The corpus however has not been extensively used for anaphora resolution research so far. In this paper, we discuss three datasets extracted from the ARRAU corpus to support the three subtasks of the CRAC 2018 Shared Task–identity anaphora resolution over ARRAU-style markables, bridging references resolution, and discourse deixis; the evaluation scripts assessing system performance on those datasets; and preliminary results on these three tasks that may serve as baseline for subsequent research in these phenomena.