In this paper, we systematically explore lexicalized and non-lexicalized local syntactic features for the task of Native Language Identification (NLI). We investigate different types of feature representations in singleand cross-corpus settings, including two representations inspired by a variationist perspective on the choices made in the linguistic system. To combine the different models, we ...

This study explores the efficacy of an approach to native language identification that utilizes grammatical, rhetorical, semantic, syntactic, and cohesive function categories comprised of key n-grams. The study found that a model based on these categories of key n-grams was able to successfully predict the L1 of essays written in English by L2 learners from 11 different L1 backgrounds with an a...

We examine different ensemble methods, including an oracle, to estimate the upper-limit of classification accuracy for Native Language Identification (NLI). The oracle outperforms state-of-the-art systems by over 10% and results indicate that for many misclassified texts the correct class label receives a significant portion of the ensemble votes, often being the runner-up. We also present a pi...

Native Language Identification (NLI) is a task aimed at determining the native language (L1) of learners of second language (L2) on the basis of their written texts. To date, research on NLI has focused on relatively small corpora. We apply NLI to the recently released EFCamDat corpus which is not only multiple times larger than previous L2 corpora but also provides longitudinal data at several...

Inference plays an important role in the learning process and it can lead to a rapid acquisition of a second language. When learning a non-native language i.e., a critical language like Arabic, the students depend on the teacher’s support most of the time to learn new concepts. The students focus on memorizing the new vocabulary and stress on learning all the grammatical rules. Hence, the stude...

This paper aims at investigating the acquisition of Italian complex predicates by native speakers of Persian. Complex predication is not as pervasive a phenomenon in Italian as it is in Persian. Yet Italian native speakers use complex predicates productively; spontaneous data show that Persian learners of Italian seem to be perfectly aware of Italian complex predicates and use this familiar fea...

In this paper, we describe the approach of the ItaliaNLP Lab team to native language identification and discuss the results we submitted as participants to the essay track of NLI Shared Task 2017. We introduce for the first time a 2-stacked sentencedocument architecture for native language identification that is able to exploit both local sentence information and a wide set of general–purpose f...

We present a system for automatically identifying the native language of a writer. We experiment with a large set of features and train them on a corpus of 9,900 essays written in English by speakers of 11 different languages. our system achieved an accuracy of 43% on the test data, improved to 63% with improved feature normalization. In this paper, we present the features used in our system, d...