Knowledge Base Completion

48 papers with code • 0 benchmarks • 1 datasets

Knowledge base completion is the task which automatically infers missing facts by reasoning about the information already present in the knowledge base. A knowledge base is a collection of relational facts, often represented in the form of "subject", "relation", "object"-triples.

Datasets


Latest papers without code

Combining Rules and Embeddings via Neuro-Symbolic AI for Knowledge Base Completion

no code yet • 16 Sep 2021

Recent interest in Knowledge Base Completion (KBC) has led to a plethora of approaches based on reinforcement learning, inductive logic programming and graph embeddings.

Inductive logic programming Knowledge Base Completion

BERTnesia: Investigating the capture and forgetting of knowledge in BERT

no code yet • 5 Jun 2021

We found that ranking models forget the least and retain more knowledge in their final layer compared to masked language modeling and question-answering.

Knowledge Base Completion LAMA +3

CEAR: Cross-Entity Aware Reranker for Knowledge Base Completion

no code yet • 18 Apr 2021

Pre-trained language models (LMs) like BERT have shown to store factual knowledge about the world.

Knowledge Base Completion Link Prediction

DOCENT: Learning Self-Supervised Entity Representations from Large Document Collections

no code yet • EACL 2021

This enables a new class of powerful, high-capacity representations that can ultimately distill much of the useful information about an entity from multiple text sources, without any human supervision.

Knowledge Base Completion Question Answering

Ranking vs. Classifying: Measuring Knowledge Base Completion Quality

no code yet • 2 Feb 2021

We randomly remove some of these correct answers from the data set, simulating the realistic scenario of real-world entities missing from a KB.

Knowledge Base Completion Model Selection

Association Rules Enhanced Knowledge Graph Attention Network

no code yet • 14 Nov 2020

However, in most existing embedding methods, only fact triplets are utilized, and logical rules have not been thoroughly studied for the knowledge base completion task.

Graph Attention Knowledge Base Completion +3

BERTnesia: Investigating the capture and forgetting of knowledge in BERT

no code yet • 19 Oct 2020

We found that ranking models forget the least and retain more knowledge in their final layer.

Knowledge Base Completion NER +1

A Survey on Graph Neural Networks for Knowledge Graph Completion

no code yet • 24 Jul 2020

Knowledge Graphs are increasingly becoming popular for a variety of downstream tasks like Question Answering and Information Retrieval.

Information Retrieval Knowledge Base Completion +2

Regex Queries over Incomplete Knowledge Bases

no code yet • 1 May 2020

In response, we develop RotatE-Box -- a novel combination of RotatE and box embeddings.

Knowledge Base Completion Link Prediction

Exploiting Structured Knowledge in Text via Graph-Guided Representation Learning

no code yet • EMNLP 2020

In contrast to existing paradigms, our approach uses knowledge graphs implicitly, only during pre-training, to inject language models with structured knowledge via learning from raw text.

Entity Linking Knowledge Base Completion +4