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Towards a Gold Standard Corpus for Variable Detection and Linking in Social Science Publications
[conference paper]
Corporate Editor
European Language Resources Association (ELRA)
Abstract In this paper, we describe our effort to create a new corpus for the evaluation of detecting and linking so-called survey variables in social science publications (e.g., "Do you believe in Heaven?"). The task is to recognize survey variable mentions in a given text, disambiguate
them, and link them... view more
In this paper, we describe our effort to create a new corpus for the evaluation of detecting and linking so-called survey variables in social science publications (e.g., "Do you believe in Heaven?"). The task is to recognize survey variable mentions in a given text, disambiguate
them, and link them to the corresponding variable within a knowledge base. Since there are generally hundreds of candidates to link to and due to the wide variety of forms they can take, this is a challenging task within NLP. The contribution of our work is the first gold standard corpus for the variable detection and linking task. We describe the annotation guidelines and the annotation process. The produced corpus is multilingual - German and English - and includes manually curated word and phrase alignments. Moreover, it includes text samples that could not be assigned to any variables, denoted as negative examples. Based on the new dataset, we conduct an evaluation of several state-of-the-art text classification and textual similarity methods. The annotated corpus is made available along with an open-source baseline system for variable mention identification and linking.... view less
Keywords
social science; publication; data; algorithm; computational linguistics
Classification
Information Science
Science of Literature, Linguistics
Free Keywords
text mining; semantic textual similarity; paraphrase detection; linking
Collection Title
Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC)
Conference
11. International Conference on Language Resources and Evaluation (LREC). Miyazaki (Japan), 2018
Document language
English
Publication Year
2018
ISBN
979-10-95546-00-9
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution-Noncommercial-No Derivative Works 4.0