Dependency Graph

material ID: dependencygraph

Related Papers

Sentence Fusion via Dependency Graph Compression

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

We present a novel unsupervised sentence fu- sion method which we apply to a corpus of bi- ographies in German. Given a group of related sentences, we align their dependency …...

44905

Dependency Parsing and Semantic Role Labeling as a Single Task

Authors: nan

Publication: TIPSTER (2009)

DOI: nan

We present a comparison between two systems for establishing syntactic and semantic depen- dencies: one that performs dependency parsing and semantic role labeling as a single task, and another that …...

29504

Layer-Based Dependency Parsing

Authors: nan

Publication: TIPSTER (2009)

DOI: nan

. In this paper, a layer-based projective dependency parsing approach is presented. This novel approach works layer by layer from the bottom up. Inside the layer the dependency graphs are …...

19347

Unsupervised Person Slot Filling based on Graph Mining

Authors: nan

Publication: TIPSTER (2016)

DOI: nan

Slot filling aims to extract the values (slot fillers) of specific attributes (slots types) for a given entity (query) from a large- scale corpus. Slot filling remains very challenging over …...

40613

Semantic Dependency Parsing via Book Embedding

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractWe model a dependency graph as a book, a particular kind of topological space, for semantic dependency parsing. The spine of the book is made up of a sequence of …...

36963

Graph Convolutional Network with Sequential Attention for Goal-Oriented Dialogue Systems

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractDomain-specific goal-oriented dialogue systems typically require modeling three types of inputs, namely, (i) the knowledge-base associated with the domain, (ii) the history of the conversation, which is a sequence of …...

26698

Cross-Task Instance Representation Interactions and Label Dependencies for Joint Information Extraction with Graph Convolutional Networks

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractExisting works on information extraction (IE) have mainly solved the four main tasks separately (entity mention recognition, relation extraction, event trigger detection, and argument extraction), thus failing to benefit from …...

21869