SEMAPRO 2018 Proceedings

In this contribution, we explore the type of linguistic knowledge that is required to establish relatedness between a claim and a justification which may be distant or in different texts, within the framework of argument mining. We propose an original annotation method based on XML-Frames and a linguistic analysis of the main resources which are needed to establish relatedness on a linguistic basis. Keywords–Argument Mining; Linguistic Knowledge; Relatedness; Annotation. I. AIMS AND MOTIVATIONS One of the main challenges of argument mining is to correctly identify the statements that are justifications or that support a given claim across different types of online texts (for example, news articles, blogs, consumer reviews). This issue is called argument relatedness and it is a central point in information retrieval. It is also essential in argument mining [1]-[3]. The main objective of research on argument relatedness is to be able to mine statements which develop the same topic as the given claim and have an argumentative orientation. Broadly speaking, relatedness is a measure of the semantic and topical proximity of two text spans. These segments may differ lexically (via the use of synonyms, hyponyms or hypernyms, to name a few possibilities) or syntactically (for example, with alternations, such as active vs. passive structures). Previous research [4] has shown that establishing relatedness between an argument and a statement requires knowledge in 58% to 88% of situations, depending on the topic of the claim. Since supports and attacks (elements that oppose a claim) of a claim mainly address the purposes, goals, functions or structure of the main concepts of the claim, previous studies have used the Qualia structure of the Generative Lexicon [5] as a knowledge representation system for relatedness. This approach pairs domain knowledge with lexical semantics in an efficient and principled way. However, this previous work also shows that Qualia structures are difficult to develop and must be defined for each topic. This makes knowledgebased argument mining an approach that, although effective, is difficult to reuse over different domains. The current research project examines and evaluates the possibility of establishing relatedness solely on the basis of linguistic knowledge and lexical semantics. The development of general-purpose linguistic processes and resources that characterize relatedness would make the implementation of relatedness much simpler and much more reusable over domains. This contribution explores this hypothesis as well as the linguistic knowledge which is required, in particular lexical semantics. The rest of the paper is structured as follows. The analysis protocol and the annotation system are presented in Section II, while Section III deals with the future steps that need to be taken to be able to establish relatedness on a linguistic basis. II. ANALYSIS PROTOCOL This research introduces two specificities. First, the analysis of relatedness is based on the topical content of the claim, as a claim-driven analysis allows the analysis to focus on the features of the claim and to integrate the new elements found in various statements related to that claim. In addition, the annotation is not based on standard linear text annotations but on the use of frames encoded in XML: the use of an XMLFrame approach is motivated by the fact that the elements found in statements and that are decisive for the analysis of the semantic elements of relatedness may not be adjacent, which makes text annotation, which is linear, almost intractable. In this framework, relevant statements are extracted from the source text and fed into XML-Frames in which the features are filled in manually by annotators. Each statement found to be related to the claim and with an argumentative orientation originates an instance of the frame. The result is a set of frames which can be organized as a tree, where the root is the frame representing the claim and the children are those statements found in texts and that introduce additional constraints on the topic. These additional constraints on the claim topic characterize relatedness. The relations of each statement with the claim are described in each frame instance through the use of features indicating the linguistic and conceptual links between the claim and the statement. Our corpus is based on texts about controversial social issues, addressing topics such as affirmative action or the gender pay gap. These are relatively complex issues, which guarantees that the need for linguistic and conceptual knowledge will be apparent. The goal is then to mine statements which are related to this claim in various texts. These statements must have a topic that is subsumed by the claim topic and an argumentative orientation which may support or attack the claim, depending on the content of the statement. The argumentative orientation is given by evaluative expressions 1 Copyright (c) IARIA, 2018. ISBN: 978-1-61208-678-1 SEMAPRO 2018 : The Twelfth International Conference on Advances in Semantic Processing