Search Results for author:
Found 11 papers, 4 papers with code
Chasing Streams with Existential Rules
We study reasoning with existential rules to perform query answering over streams of data.
Tribrid: Stance Classification with Neural Inconsistency Detection
In the second case, we show that using the confidence scores to remove doubtful predictions allows our method to achieve human-like performance over the retained information, which is still a sizable part of the original input.
Tab2Know: Building a Knowledge Base from Tables in Scientific Papers
First, our pipeline applies weakly supervised classifiers to recognize the type of tables and columns, with the help of a data labeling system and an ontology specifically designed for our purpose.
Materializing Knowledge Bases via Trigger Graphs
The chase is a well-established family of algorithms used to materialize Knowledge Bases (KBs), like Knowledge Graphs (KGs), to tackle important tasks like query answering under dependencies or data cleaning.
Checking Chase Termination over Ontologies of Existential Rules with Equality
Therefore, one can apply existing acyclicity notions to check chase termination over an axiomatisation of an ontology and then use the original ontology for reasoning.
Datalog Reasoning over Compressed RDF Knowledge Bases
Materialisation is often used in RDF systems as a preprocessing step to derive all facts implied by given RDF triples and rules.
Extracting Novel Facts from Tables for Knowledge Graph Completion (Extended version)
We propose a new end-to-end method for extending a Knowledge Graph (KG) from tables.
A Deep Dive into Word Sense Disambiguation with LSTM
LSTM-based language models have been shown effective in Word Sense Disambiguation (WSD).
Word Sense Disambiguation with LSTM: Do We Really Need 100 Billion Words?
Recently, Yuan et al. (2016) have shown the effectiveness of using Long Short-Term Memory (LSTM) for performing Word Sense Disambiguation (WSD).
KOGNAC: Efficient Encoding of Large Knowledge Graphs
We propose KOGNAC, a dictionary-encoding algorithm designed to improve SPARQL querying with a judicious combination of statistical and semantic techniques.
Column-Oriented Datalog Materialization for Large Knowledge Graphs (Extended Technical Report)
The evaluation of Datalog rules over large Knowledge Graphs (KGs) is essential for many applications.
