GRaSP: A Multilayered Annotation Scheme for Perspectives

GRaSP: A Multilayered Annotation Scheme for Perspectives Chantal van Son, Tommaso Caselli, Antske Fokkens, Isa Maks, Roser Morante, Lora Aroyo and Piek Vossen Vrije Universiteit Amsterdam De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands {c.m.van.son, t.caselli, antske.fokkens, isa.maks, r.morantevallejo, lora.aroyo, piek.vossen}@vu.nl Abstract This paper presents a framework and methodology for the annotation of perspectives in text. In the last decade, different aspects of linguistic encoding of perspectives have been targeted as separated phenomena through different annotation initiatives. We propose an annotation scheme that integrates these different phenomena. We use a multilayered annotation approach, splitting the annotation of different aspects of perspectives into small subsequent subtasks in order to reduce the complexity of the task and to better monitor interactions between layers. Currently, we have included four layers of perspective annotation: events, attribution, factuality and opinion. The annotations are integrated in a formal model called GRaSP, which provides the means to represent instances (e.g. events, entities) and propositions in the (real or assumed) world in relation to their mentions in text. Then, the relation between the source and target of a perspective is characterized by means of perspective annotations. This enables us to place alternative perspectives on the same entity, event or proposition next to each other. Keywords: source perspective, multilayered annotation, attribution 1. Introduction With the Internet having secured an increasingly prominent place in society, the current age is characterized by the abil- ity of individuals to transfer and access information about the world. The textual form in which this information is usually represented is rich and complex. Texts contain in- formation about what is happening in the world, where, when, and who is involved. At the same time, they are a reflection of ongoing debates in our society, stances on particular issues (e.g. abortion, vaccinations, etc.), and in- terpretative frames on events and their causes (e.g. conspir- acy theories on 9/11). Textual data always provide specific perspectives of the author and quoted sources on the infor- mation they contain. Mining information from texts thus implies dealing with these perspectives. In the last decade, different aspects of linguistic encoding of perspectives have been targeted as separated phenom- ena through different annotation initiatives, each with its own approaches and goals. Targeted aspects of perspec- tives include, for example, attribution (Prasad et al., 2007; Pareti, 2012), factuality (Saur´ı and Pustejovsky, 2009; Diab et al., 2009), and opinion (Wiebe et al., 2005). Coordi- nating initiatives such as the Unified Linguistic Annotation project1 have tried to technically combine such annotations into a unique annotation model, but they lack an overarch- ing framework for the various layers of annotation from dif- ferent resources. Furthermore, annotation initiatives such as those proposed by Prasad et al. (2007) and Pareti (2012) have attempted to tackle the annotation of perspectives in a unified approach, but with different levels of success.2 In our approach, the notion of perspectives lies at the semantic-pragmatic interface. A perspective of a given source consists of a statement that is made (what is said or …

Content truncated to 500 words