Neural networks are the state-of-the-art method of machine learning for many problems in
NLP. Their success in machine translation and other NLP tasks is phenomenal, but their …

We present a method for supervised cross-lingual construction of word-formation networks
(WFNs). WFNs are resources capturing derivational, compositional and other relations …

The paper contains the description of a semi-authomatic method for the detection of
typologically relevant semantic shifts in the world's languages. The algorithm extracts …

We present COSTRA 1.0, a dataset of complex sentence transformations. The dataset is
intended for the study of sentence-level embeddings beyond simple word alternations or …

Abstract Words in natural language can be assigned to specific morphological categories.
For example, the English word 'apples' can be described using morphological labels like N; …

Turkish is an agglutinating language relying almost exclusively on suffixation. Most suffixes,
especially derivational ones, carry a distinctive meaning content blending with the base …

We investigate to what extent inflection can be automatically separated from derivation, just
based on the word forms. We expect pairs of inflected forms of the same lemma to be closer …

In agglutinating languages such as Turkish, the process of derivation is mostly performed by
adding suffixes at the end of words. Most of the derivational suffixes carry a distinctive …

Building on an extensive review of the psycholinguistics literature and Turkish Derivational
Morphology (DM), we propose a novel structure for representing DM in three hierarchical …

In this article, we take a new look on automated analysis and recognition of morpho-
semantic relations in Polish. We present a combination of two methods for join exploration …