Annotating Content Zones in News Articles
Authors: Daniela Baiamonte, Tommaso Caselli, Irina Prodanof (Università di Pavia, VU Amsterdam, 2016)
Topic: Lexical and Semantic Resources and Analysis

Abstract
This paper presents a methodology for the annotation of the semantic and functional components of news articles (Content Zones, henceforth CZs). We distinguish between narrative and descriptive zones and, within them, among finer-grained units contributing to the overall communicative purpose of the text. Furthermore, we show that the segmentation in CZs could provide valuable cues for the recognition of time relations between events.

Introduction
The logical structure of a document, i.e. its hierarchical arrangement in sections, paragraphs, sentences and the like, reflects a functional organization of the information flow and creates expectations on where the desired information may be located. As it is often the case, however, breakups in sections and paragraphs are motivated by style or even arbitrary choices. The segmentation of the text in Content Zones (CZs, henceforth), i.e. functional categories contributing to the overall message or purpose, as induced by the genre of the text, provides more reliable and fine-grained cues to access the structure of its types of functional content. Previous attempts to annotate CZs have mainly focused on highly standardized texts like scientific articles AUTHOR and scheduling dialogues AUTHOR, or on semi-structured texts AUTHOR like film reviews AUTHOR. Other work AUTHOR adopts the theory of discourse modes AUTHOR to distinguish between the different types of text passages in a text document. To the best of our knowledge, no efforts have been undertaken to devise an annotation scheme targeting the functional structure of news articles in terms of their content: the inverted pyramid structure, i.e. the gathering of key details at the beginning, followed by supporting information in order of diminishing importance, is too coarse-grained to be effectively used for information extraction purposes. Our hypothesis is that modeling the document's content via CZs could yield benefits for high-level NLP tasks such as Temporal Processing, Summarization, Question-Answering, among others. In addition to this, CZs qualify as a higher-level analysis of a text/discourse which captures different information with respect to Discourse Relations. The remainder of the paper is structured as follows: in Section 2 the motivations of this work are presented, together with related studies. Section 3 reports on our inventory of CZs, used to annotate a corpus of English news articles. Details on the corpus are provided in Section 4. In Section 5, we describe a case-study on the correlation between CZs and temporal relations to show that the segmentation in CZs can provide cues in recognizing temporal relations between events. Finally, Section 6 draws on conclusion and suggests directions for future work.

Conclusion
We have developed an inventory of zone labels for the genre news article and shown that the so-generated content structure could help narrowing down the range of time relations connecting events. Future work would involve testing the stability and reproducibility of the annotation scheme through the measurement of inter-annotator agreement and elaborating a separate annotation scheme for editorials, whose argumentative style reflects different structuring principles than those acting in news reports. Finally, we would like to automatize the process of annotation and test the effectiveness of the approach in texts belonging to different genres, e.g. novels AUTHOR and historical essays. Even the basic distinction between narrative and descriptive zones could facilitate the performance of more complex NLP tasks by targeting the relevant informational zones. The corpus and the annotation guidelines are publicly available.