Using Cross-Lingual Part of Speech Tagging for Partially Reconstructing the Classic Language Family Tree Model

Abstract

The tree model is well known for expressing the historic evolution of languages. This model has been considered as a method of describing genetic relationships between languages. Nevertheless, some researchers question the model's ability to predict the proximity between two languages, since it represents genetic relatedness rather than linguistic resemblance. Defining other language proximity models has been an active research area for many years. In this paper we explore a part-of-speech model for defining proximity between languages using a multilingual language model that was fine-tuned on the task of cross-lingual part-of-speech tagging. We train the model on one language and evaluate it on another; the measured performance is then used to define the proximity between the two languages. By further developing the model, we show that it can reconstruct some parts of the tree model.

Column-Type Prediction for Web Tables Powered by Knowledge Base and Text

“…While searching for its text description, we get an entire paragraph of sentences, as shown in Figure 7. Then, we adopt part-of-speech tagging tools [24][25][26] to extract keywords which may be the entities or classes, such as "open-source hardware", "software company", "digital devices", "microcontrollers", and "kits". From the example, we can infer that an in-depth description of an entity can be obtained by extracting unstructured text from the KB.…”