2023年度 人工知能学会全国大会(第37回)

2023年度 人工知能学会全国大会(第37回)

2023年6月6日〜6月9日熊本城ホール(熊本県熊本市) + オンライン
人工知能学会
2023年度 人工知能学会全国大会(第37回)

2023年度 人工知能学会全国大会(第37回)

2023年6月6日〜6月9日熊本城ホール(熊本県熊本市) + オンライン

[2U1-IS-1b-05]Anaphora and semantic resolution by introducing multitasking into coreference algorithms

〇Theo Jean Poncelet1, Tomoyuki Maekawa1, Michita Imai1(1. Keio University)
[[Online, Regular]]
While the world of bridging anaphora resolution (BAR) is ruled by the multi-task algorithms, they are used to only perform BAR and not coreference resolution (CR). Furthermore, their pipelines are very demanding in terms of computational and spatial resources. We therefore propose to use the work of Dobrovolskii (2021) on CR and Yu and Poesio (2020) on multi-task BAR to create a multi-task and efficient algorithm that will be able to resolve both BAR and CR at the same time. We also demonstrate that, on top of its efficiency, the results of our algorithm are still competitive both in BAR and in CR with recent works.