Typhoon　disasters　not　only　trigger　secondary　disasters,　such　as　rainstorms　and　flooding,　but　also　bring　many　negative　impacts　on　the　normal　operation　of　urban　infrastructure　and　the　safety　of　people’s　lives　and　property.　In　order　to　effectively　prevent　the　risks　of　typhoon　disaster　chain,　this　paper　proposes　a　joint　entity　and　relation　extraction　model　based　on　RoBERTa-Adv-GPLinker.　Then,　relying　on　the　ontology　theory　and　methodology,　we　establish　a　knowledge　graph　of　typhoon　disaster　chain.　The　results　show　that　the　joint　extraction　model　based　on　RoBERTa-Adv-GPLinker　outperforms　other　baseline　models　in　all　assessment　indexes.　Moreover,　the　constructed　knowledge　graph　of　typhoon　disaster　chain　includes　secondary　disasters　and　derived　disaster　impacts.　This　can　largely　depict　the　evolution　process　of　typhoon　disaster　secondary　derivations.　On　this　basis,　a　risk　assessment　model　of　typhoon　disaster　chain　based　on　Bayesian　network　is　established.　Taking　Fujian　Province　as　an　example,　the　risk　associated　with　the　typhoon　disaster　chain　is　assessed,　verifying　the　effectiveness　of　the　method.　This　study　provides　a　scientific　basis　for　enhancing　government　emergency　response　capabilities　and　achieving　sustainable　regional　development.　©　2025　by　the　authors.