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Document-level relation extraction (DocRE) aims to extract relations among entities across multiple sentences within a document by using reasoning skills (i.e., pattern recognition, logical reasoning, coreference reasoning, etc.) related to the reasoning paths between two entities.
Relation Extraction is the task of predicting attributes and relations for entities in a sentence. For example, given a sentence ?Barack Obama was born in Honolulu, Hawaii.?, a relation classifier aims at predicting the relation of ?bornInCity?.
Subgraph Extraction In document-level RE, there could be multiple relations be- tween an entity pair, corresponding to multiple reasoning paths. In addition, determining a single implicit relation may also require multiple reasoning paths.
Relation Extraction (RE) is the task of extracting semantic relationships from text, which usually occur between two or more entities. These relations can be of different types. E.g ?Paris is in France? states a ?is in? relationship from Paris to France. This can be denoted using triples, (Paris, is in, France).