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New article on meta-knowledge enrichment of news-related events

2016-02-16

We are pleased to announce the publication of a new journal article describing the creation of a new annotation effort, which is aimed at facilitating the automatic extraction of information relating to varuious apects of the interpretation of events (meta-knowledge) in news-related documents. We have annotated six different types of meta-knowledge attributes for each of the 5349 events within the 599 documents of the ACE 2005 corpus. We have aditionally annotated textual cues that provide evidence for the assignment of the different attributes.

Thompson, P., Nawaz, R., McNaught, J. and Ananiadou, S. (2016). Enriching News Events with Meta-knowledge Information. Language Resources and Evaluation. DOI: 10.1007/s10579-016-9344-9

Abstract

Given the vast amounts of data available in digitised textual form, it is important to provide mechanisms that allow users to extract nuggets of relevant information from the ever growing volumes of potentially important documents. Text mining techniques can help, through their ability to automatically extract relevant event descriptions, which link entities with situations described in the text. However, correct and complete interpretation of these event descriptions is not possible without considering additional contextual information often present within the surrounding text. This information, which we refer to as meta-knowledge, can include (but is not restricted to) the modality, subjectivity, source, polarity and specificity of the event. We have developed a meta-knowledge annotation scheme specifically tailored for news events, which includes six aspects of event interpretation. We have applied this annotation scheme to the ACE 2005 corpus, which contains 599 documents from various written and spoken news sources. We have also identified and annotated the words and phrases evoking the different types of meta-knowledge. Evaluation of the annotated corpus shows high levels of inter-annotator agreement for five meta-knowledge attributes, and moderate level of agreement for the sixth attribute. Detailed analysis of the annotated corpus has revealed further insights into the expression mechanisms of different types of meta-knowledge, their relative frequencies and mutual correlations.

Resource availability

The annotations, guidelines, updated DTD for ACE 2005 (incorporating meta-knowledge information), and a a Java program to integrate the meta-knowleddge annotations with existing ACE 2005 annotations, are available via the ACE Meta-knowledge annotation page.