expressions in Japanese are obligatory in English 3 妻が 息⼦に いくつか おもちゃを 買ってあげた 。ϕ! =NOM ⾚い ⾞を 特に 気に⼊っている 。 wife=NOM several son=DAT toy=ACC red buy.GER=give.PST especially 𝜙! =NOM like.GER=be.NPST car=ACC My wife got my son several toys. He especially likes the red car.
気に⼊っている 。 Existing Approaches 4 • A line of research tried rule-based methods to annotate translation pairs with ZAR annotation (Nakaiwa, 1999; Furukawa+, 17) • Rely on word alignment, dependency parsing, and coreference resolution • However, their methods met limitation due to error propagation nsubj Coreference Word alignment My wife got my son several toys. He especially likes the red car.
learning from MT • By generating English sentence, the MT model is forced to implicitly recover ZP • Toward the discrepancy between MT(encoder-decoder) and ZAR(encoder), we adopt BERT-based method • To mitigate catastrophic forgetting, we test to incorporate masked language modeling (MLM) during MT
antecedent was successfully identified OURS BASELINE GOLD Source Text Translation by model 第七⼗四回 全国 ⾼校 ラグビー フットボール ⼤会 準決勝の 五⽇ 、 近鉄花園ラグビー場の スタンドでは ϕ! -NOM 同 ラグビー 場から わずか ⼀・五キロの ⾄近距離に あり ながら 、 .. same rugby 𝜙! -NOM 1.5km=GEN distance=DAT be-GER only Twenty-two students of Osaka Korean pro-Pyongyang Korean high school students watched the final at Kintetsu National High School's Hanazono Stadium on Sunday . Although the school is only about five kilometers away from the stadium, .. ORD 74 CLF rugby national high.school football tournament semi final=GEN 5day Kintetsu Hanazono rugby field=GEN stands=LOC=TOP Osaka korea high school 25 CLF=NOM blue wind breaker rugby club.member appearance=INS watch=do.PST field=ABL but ⼤阪 朝鮮 ⾼級学校 ラグビー 部員 ⼆⼗五⼈が ⻘い ウインドブレーカー 姿で 観戦した。
Our experiments show that ZAR can benefit from parallel texts thanks to the flexibility of neural networks • Our framework revived the old idea(1999!) • In addition, we find further gains can be obtained by incorporating MLM 10