WiSe 2024/25

This course introduces several different theories of semantic annotation, including UD, semantic roles, frame semantics, AMR, and parallel meaning bank. The students will learn the theoretical backgrounds and the detailed annotation schemas, and gain some experience in annotating the real-life data, both manually and automatically.

To get BN, one should finish at least 60% of the homework successfully. To get AP, one should also pass a written exam.

In this seminar, we look into a variety of approaches to data-driven parsing that extend standard constituency parsers in different ways:
1. We will discuss approaches that are based on grammar formalisms that are able to generate structures that are beyond context-free grammars. Examples are LCFRS and TAG. Topics in this context are grammar extraction, supertagging and various parsing methods.
2. Related to this, we will discuss approaches that are able to describe discontinuous constituents. These can be grammar-based (LCFRS) or transition based parsers with appropriate transitions such as gap or swap.
3. The course will also cover aspects of incremental, cognitively plausible approaches to constituency parsing.