Comunicació presentada a: the Fourth International Conference on Dependency Linguistics (Depling 2017), celebrada a Pisa, Itàlia, del 18 al 20 de setembre 2017.

In this paper, we present a revision of the training set of the METU-Sabancı Turkish syntactic dependency treebank composed of 4997 sentences in accordance with the principles of the Meaning-Text Theory (MTT). MTT reflects the multilayered nature of language by a linguistic model in which each linguistic phenomenon is treated at its corresponding level(s). Our analysis of the METU-Sabancı syntactic relation tagset reveals that it encodes deepmorphological and surface-syntactic phenomena, which should be separated according to the MTT model. We propose an alternative surface-syntactic relation annotation schema and show that this schema also allows for a sound projection of the obtained surface annotation onto a deepsyntactic annotation, as needed for the implementation of down-stream language understanding applications.

The presented work has been funded by the European Commission as part of the H2020 Programme, under the contract numbers 645012–RIA and 700024-RIA.