- Katharina Probst, Lori S. Levin. 2002. Challenges in automated elicitation of a controlled bilingual corpus.. Abstract: In this paper we will address an uncommon but important approach to automated learning for MT, namely learning of translation rules from carefully elicited sentences. The approach is uncommon for good reason — anyone who has tried linguistic field work knows that elicitation will go awry if not carefully monitored by a human. We will address eight challenges of automated elicitation and discuss their solution in the AVENUE machine translation project. The elicited sentences in AVENUE are used to semi-automatically infer transfer rules for the desired language pair.
