Extracting Relations Within and Across Sentences

Previous work on relation extraction has focussed on identifying relationships between entities that occur in the same sentence (intra-sentential relations) rather than between entities in different sentences (inter-sentential relations) despite previous research having shown that intersentential relations commonly occur in information extraction corpora. This paper describes a SVM-based approach to relation extraction that is applied to both types. Adapted features and techniques for counter-acting bias in SVM models are used to deal with specific issues that arise in the inter-sentential case. It was found that the structured features used for intrasentential relation extraction can be easily adapted for the inter-sentential case and provides comparable performance.