Publications

Abstract

We report a hitherto unknown statistical relationship between the corpus frequency of finite verbs and their fixed linear positions (early vs. late) in finite clauses of English, Dutch, and German. Compared to the overall frequency distribution of verb lemmas in the corpora, high-frequency finite verbs are overused in main clauses, at the expense of nonfinite verbs. This finite versus nonfinite split of high-frequency verbs is basically absent from subordinate clauses. Furthermore, this “main-clause bias” (MCB) of high-frequency verbs is more prominent in German and Dutch (SOV languages) than in English (an SVO language). We attribute the MCB and its varying effect sizes to faster accessibility of high-frequency finite verbs, which (1) increases the probability for these verbs to land in clauses mandating early verb placement, and (2) boosts the activation of clause plans that assign verbs to early linear positions (in casu: clauses with SVO as opposed to SOV order).

Abstract

Students who are learning to write in a foreign language, often want feedback on the grammatical quality of the sentences they produce. The usual NLP approach to this problem is based on parsing student-generated text. Here, we propose a generation-based ap- proach aiming at preventing errors ("scaffolding"). In our ICALL system, the student constructs sentences by composing syntactic trees out of lexically anchored "treelets" via a graphical drag & drop user interface. A natural-language generator computes all possible grammatically well-formed sentences entailed by the student-composed tree. It provides positive feedback if the student-composed tree belongs to the well-formed set, and negative feedback otherwise. If so requested by the student, it can substantiate the positive or negative feedback based on a comparison between the student-composed tree and its own trees (informative feedback on demand). In case of negative feedback, the system refuses to build the structure attempted by the student. Frequently occurring errors are handled in terms of "malrules." The system we describe is a prototype (implemented in JAVA and C++) which can be parameterized with respect to L1 and L2, the size of the lexicon, and the level of detail of the visually presented grammatical structures.