1. Rule Learning – Overview Goal: learn transfer rules for a language pair where one language is resource-rich, the other is resource-poor Learning proceeds in three steps: 1.Flat Seed Generation: informed guessing of transfer rules 2.Compositionality: adding structure to rules, using previously learned rules 3.Seeded Version Space Learning: generalizing rules to make them scale to more unseen examples

2. S::S [det adv adj n aux neg v det n] [det adv adj n v det n neg vpart] (;;alignments: (x1:y1)(x2::y2)(x3::y3)(x4::y4)(x6::y8)(x7::y5)(x7::y9)(x8::y6)(x9::y7)) ;;constraints: ((x1 def) = *+) ((x4 agr) = *3-sing) ((x5 tense) = *past) …. ((y1 def) = *+) ((y3 case) = *nom) ((y4 agr) = *3-sing) …. ) The highly qualified applicant did not accept the offer. Der äußerst qualifizierte Bewerber nahm das Angebot nicht an. ((1,1),(2,2),(3,3),(4,4),(6,8),(7,5),(7,9),(8,6),(9,7)) Flat Seed Generation - Example

3. S::S [det adv adj n aux neg v det n] [det adv adj n v det n neg vpart] (;;alignments: (x1:y1)(x2::y2)(x3::y3)(x4::y4)(x6::y8)(x7::y5)(x7::y9)(x8::y6)(x9::y7) ;;constraints: ((x1 def) = *+) ((x4 agr) = *3-sing) ((x5 tense) = *past) …. ((y1 def) = *+) ((y3 case) = *nom) ((y4 agr) = *3-sing) …. ) S::S [NP aux neg v det n] [NP v det n neg vpart] (;;alignments: (x1::y1)(x3::y5)(x4::y2)(x4::y6)(x5::y3)(x6::y4) ;;constraints: ((x2 tense) = *past) …. ((y1 def) = *+) ((y1 case) = *nom) …. ) NP::NP [det AJDP n] [det ADJP n] ((x1::y1)… ((y3 agr) = *3-sing) ((x3 agr = *3-sing) ….) Compositionality - Example

4. S::S [NP aux neg v det n] [NP v det n neg vpart] (;;alignments: (x1::y1)(x3::y5)(x4::y2)(x4::y6)(x5::y3)(x6::y4) ;;constraints: ((x2 tense) = *past) …. ((y1 def) = *+) ((y1 case) = *nom) ((y1 agr) = *3-sing) … ) ((y3 agr) = *3-sing) ((y4 agr) = *3-sing)… ) S::S [NP aux neg v det n] [NP v det n neg vpart] (;;alignments: (x1::y1)(x3::y5)(x4::y2)(x4::y6)(x5::y3)(x6::y4) ;;constraints: ((x2 tense) = *past) … ((y1 def) = *+) ((y1 case) = *nom) ((y1 agr) = *3-plu) … ((y3 agr) = *3-plu) ((y4 agr) = *3-plu)… ) S::S [NP aux neg v det n] [NP n det n neg vpart] ( ;;alignments: (x1::y1)(x3::y5) (x4::y2)(x4::y6) (x5::y3)(x6::y4) ;;constraints: ((x2 tense) = *past) … ((y1 def) = *+) ((y1 case) = *nom) ((y4 agr) = (y3 agr)) … ) Seeded Version Space Learning - Example

5. Remaining Research Issues Improvement of existing algorithms Reversal of translation direction Learning with less information on the resource-poor language Learning from an unstructured corpus