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Found 13 papers, 3 papers with code
A State-transition Framework to Answer Complex Questions over Knowledge Base
Although natural language question answering over knowledge graphs have been studied in the literature, existing methods have some limitations in answering complex questions.
Overview of the CCKS 2019 Knowledge Graph Evaluation Track: Entity, Relation, Event and QA
Knowledge graph models world knowledge as concepts, entities, and the relationships between them, which has been widely used in many real-world tasks.
Sensing population distribution from satellite imagery via deep learning: model selection, neighboring effect, and systematic biases
The rapid development of remote sensing techniques provides rich, large-coverage, and high-temporal information of the ground, which can be coupled with the emerging deep learning approaches that enable latent features and hidden geographical patterns to be extracted.
NAMER: A Node-Based Multitasking Framework for Multi-Hop Knowledge Base Question Answering
We present NAMER, an open-domain Chinese knowledge base question answering system based on a novel node-based framework that better grasps the structural mapping between questions and KB queries by aligning the nodes in a query with their corresponding mentions in question.
Crake: Causal-Enhanced Table-Filler for Question Answering over Large Scale Knowledge Base
Semantic parsing solves knowledge base (KB) question answering (KBQA) by composing a KB query, which generally involves node extraction (NE) and graph composition (GC) to detect and connect related nodes in a query.
gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpus
Furthermore, we also design a cloud-based self-adaptive task scheduling for gBuilder to ensure its scalability on large-scale knowledge graph construction.
VGStore: A Multimodal Extension to SPARQL for Querying RDF Scene Graph
Semantic Web technology has successfully facilitated many RDF models with rich data representation methods.
TopoBERT: Plug and Play Toponym Recognition Module Harnessing Fine-tuned BERT
Extracting precise geographical information from textual contents is crucial in a plethora of applications.
ADMUS: A Progressive Question Answering Framework Adaptable to Multiple Knowledge Sources
With the introduction of deep learning models, semantic parsingbased knowledge base question answering (KBQA) systems have achieved high performance in handling complex questions.
Two is Better Than One: Answering Complex Questions by Multiple Knowledge Sources with Generalized Links
Incorporating multiple knowledge sources is proven to be beneficial for answering complex factoid questions.
LLMaAA: Making Large Language Models as Active Annotators
Recently, the superior few-shot performance of large language models (LLMs) has propelled the development of dataset generation, where the training data are solely synthesized from LLMs.
