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We study automatic Contract Clause Extraction (CCE) by modeling implicitrelations in legal contracts. Existing CCE methods mostly treat contracts asplain text, creating a substantial barrier to understanding contracts of highcomplexity. In this work, we first comprehensively analyze the complexityissues of contracts and distill out three implicit relations commonly found incontracts, namely, 1) Long-range Context Relation that captures thecorrelations of distant clauses; 2) Term-Definition Relation that captures therelation between important terms with their corresponding definitions; and 3)Similar Clause Relation that captures the similarities between clauses of thesame type. Then we propose a novel framework ConReader to exploit the abovethree relations for better contract understanding and improving CCE.Experimental results show that ConReader makes the prediction moreinterpretable and achieves new state-of-the-art on two CCE tasks in bothconventional and zero-shot settings.

ConReader: Exploring Implicit Relations in Contracts for Contract Clause Extraction