Knowledge Base Completion

45 papers with code • 0 benchmarks • 0 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 with code

Knowledge Base Completion Meets Transfer Learning

vid-koci/kbctransferlearning 30 Aug 2021

The aim of knowledge base completion is to predict unseen facts from existing facts in knowledge bases.

Knowledge Base Completion Transfer Learning

1
30 Aug 2021

Scientific Language Models for Biomedical Knowledge Base Completion: An Empirical Study

rahuln/lm-bio-kgc 17 Jun 2021

Biomedical knowledge graphs (KGs) hold rich information on entities such as diseases, drugs, and genes.

Knowledge Base Completion Knowledge Graphs +1

23
17 Jun 2021

QuatDE: Dynamic Quaternion Embedding for Knowledge Graph Completion

hopkin-ghp/QuatDE 19 May 2021

Knowledge graph embedding has been an active research topic for knowledge base completion (KGC), with progressive improvement from the initial TransE, TransH, RotatE et al to the current state-of-the-art QuatE.

Knowledge Base Completion Knowledge Graph Completion +2

4
19 May 2021

Modelling General Properties of Nouns by Selectively Averaging Contextualised Embeddings

lina-luck/rosv_ijcai21 4 Dec 2020

While the success of pre-trained language models has largely eliminated the need for high-quality static word vectors in many NLP applications, such vectors continue to play an important role in tasks where words need to be modelled in the absence of linguistic context.

Knowledge Base Completion

0
04 Dec 2020

IntKB: A Verifiable Interactive Framework for Knowledge Base Completion

bernhard2202/intkb COLING 2020

(ii) Our system is designed such that it continuously learns during the KB completion task and, therefore, significantly improves its performance upon initial zero- and few-shot relations over time.

Knowledge Base Completion Question Answering

4
01 Dec 2020

Explaining Neural Matrix Factorization with Gradient Rollback

carolinlawrence/gradient-rollback 12 Oct 2020

Moreover, we show theoretically that the difference between gradient rollback's influence approximation and the true influence on a model's behavior is smaller than known bounds on the stability of stochastic gradient descent.

Influence Approximation Knowledge Base Completion +1

10
12 Oct 2020

BoxE: A Box Embedding Model for Knowledge Base Completion

ralphabb/BoxE NeurIPS 2020

Knowledge base completion (KBC) aims to automatically infer missing facts by exploiting information already present in a knowledge base (KB).

Knowledge Base Completion Knowledge Graphs +1

22
13 Jul 2020

Lossless Compression of Structured Convolutional Models via Lifting

GustikS/NeuraLogic ICLR 2021

The computation graphs themselves then reflect the symmetries of the underlying data, similarly to the lifted graphical models.

Knowledge Base Completion

17
13 Jul 2020

Temporal Knowledge Base Completion: New Algorithms and Evaluation Protocols

dair-iitd/tkbi EMNLP 2020

Temporal knowledge bases associate relational (s, r, o) triples with a set of times (or a single time instant) when the relation is valid.

Knowledge Base Completion Knowledge Graph Completion +4

12
02 May 2020

Knowledge Base Completion: Baseline strikes back (Again)

dair-iitd/kbc-baseline 2 May 2020

Most existing methods train with a small number of negative samples for each positive instance in these datasets to save computational costs.

Knowledge Base Completion Knowledge Base Population +3

0
02 May 2020