text1: To address these concerns, we supplement our Base Estimate of benefits with a series of sensitivity calculations that make use of other sources of concentration-response and valuation data for key benefits categories.
feat_premise_binary_parse: ( ( To ( address ( these concerns ) ) ) ( , ( we ( ( supplement ( ( ( our ( Base Estimate ) ) ( of ( benefits ( with ( ( a series ) ( of ( sensitivity calculations ) ) ) ) ) ) ) ( that ( make ( use ( of ( ( other sources ) ( of ( ( concentration-response ( and ( valuation data ) ) ) ( for ( key ( benefits categories ) ) ) ) ) ) ) ) ) ) ) ) . ) ) ) )
feat_premise_parse: (ROOT (S (S (VP (TO To) (VP (VB address) (NP (DT these) (NNS concerns))))) (, ,) (NP (PRP we)) (VP (VBZ supplement) (NP (NP (PRP$ our) (NNP Base) (NNP Estimate)) (PP (IN of) (NP (NP (NNS benefits)) (PP (IN with) (NP (NP (DT a) (NN series)) (PP (IN of) (NP (NN sensitivity) (NNS calculations))))))) (SBAR (WHNP (WDT that)) (S (VP (VBP make) (NP (NP (NN use)) (PP (IN of) (NP (NP (JJ other) (NNS sources)) (PP (IN of) (NP (NP (NN concentration-response) (CC and) (NN valuation) (NNS data)) (PP (IN for) (NP (JJ key) (NNS benefits) (NNS categories))))))))))))) (. .)))
text2: Each estimate is created without bias.
feat_hypothesis_binary_parse: ( ( Each estimate ) ( ( is ( created ( without bias ) ) ) . ) )
feat_hypothesis_parse: (ROOT (S (NP (DT Each) (NN estimate)) (VP (VBZ is) (VP (VBN created) (PP (IN without) (NP (NN bias))))) (. .)))