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Creating a Gold Standard Corpus for the Extraction of Chemistry-Disease Relations from Patent Texts

This paper describes the creation of a gold standard for chemistry-disease relations in patent texts. We start with an automated annotation of named entities of the domains chemistry (e.g. “propranolol”) and diseases (e.g. “hypertension”) as well as of related domains like methods and substances. After that, domain-relevant relations between these entities, e.g. “propranolol treats hypertension”, have been manually annotated. The corpus is intended to be suitable for developing and evaluating relation extraction methods. In addition, we present two reasoning methods of high precision for automatically extending the set of extracted relations. Chain reasoning provides a method to infer and integrate additional, indirectly expressed relations occurring in relation chains. Enumeration reasoning exploits the frequent occurrence of enumerations in patents and automatically derives additional relations. These two methods are applicable both for verifying and extending the manually annotated data as well as for potential improvements of automatic relation extraction.