Search Results for author:
Found 10 papers, 2 papers with code
Named Entity Recognition for Nepali Language
Named Entity Recognition have been studied for different languages like English, German, Spanish and many others but no study have focused on Nepali language.
Knowledge Graph Fact Prediction via Knowledge-Enriched Tensor Factorization
We present a family of novel methods for embedding knowledge graphs into real-valued tensors.
Team UMBC-FEVER : Claim verification using Semantic Lexical Resources
We describe our system used in the 2018 FEVER shared task.
SURFACE: Semantically Rich Fact Validation with Explanations
Judging the veracity of a sentence making one or more claims is an important and challenging problem with many dimensions.
Jointly Identifying and Fixing Inconsistent Readings from Information Extraction Systems
KGCleaner is a framework to identify and correct errors in data produced and delivered by an information extraction system.
UMBC at SemEval-2018 Task 8: Understanding Text about Malware
We describe the systems developed by the UMBC team for 2018 SemEval Task 8, SecureNLP (Semantic Extraction from CybersecUrity REports using Natural Language Processing).
Formal Ontology Learning from English IS-A Sentences
Ontology learning (OL) is the process of automatically generating an ontological knowledge base from a plain text document.
Description Logics based Formalization of Wh-Queries
The problem of Natural Language Query Formalization (NLQF) is to translate a given user query in natural language (NL) into a formal language so that the semantic interpretation has equivalence with the NL interpretation.
Formal Ontology Learning on Factual IS-A Corpus in English using Description Logics
Hence, we also claim that such sentences requires special studies in the context of OL before any truly formal OL can be proposed.
DLOLIS-A: Description Logic based Text Ontology Learning
Researchers in this field have been motivated by the possibility of automatically building a knowledge base on top of text documents so as to support reasoning based knowledge extraction.
