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Figure 1: We leverage semantic information to unify the representation of entities and relations. Relational triples are extracted by modeling the entity-entity inter- action (blue dashed line) and entity-relation interaction (red solid line) in a unied way. to jointly extract <s-r-o> triples in an end-to-end manner. CCL23-Eval ûûû ¡ ¡ ¡ 1ûûû ßßß ¥¥¥ JJJ úúú Ï Ï Ï ­ ­ ­ ÃÃÃ ùùù f f f ` ` ` äää MMM }} } SSS Æ Æ Æ +++ NNN QQQ - ý å F ö L / ¬ BISTU-IIIP / ¬ [email protected] óóó ûûû BISTU-IIIP / ¬ [email protected] 3ê33êê (ããã.) (ÑÑÑ.) d. Source Code (tï1iJ) b. DVD (4)HRlS Requirement(îlïno 00. (Organization Structure) , (Employee Information) , (Performance) ( ) låLLTi DataPro, Humanica, Hardware Fin Software Fimj Total u 1 400 000 1 700 000 1 800 000 500 000 600 000 6 …

untitled. construct a training corpus for speech entity recognition. For problem (2), this paper proposes to use the pre-trained language model to re-score the N-BEST list of speech named entity recognition, and use the external knowledge in the pre-trained model to help the end-to-end model select the best result.

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