Knowledge Base Population

32 papers with code • 1 benchmarks • 3 datasets

Knowledge base population is the task of filling the incomplete elements of a given knowledge base by automatically processing a large corpus of text.

Most implemented papers

A Dataset for Web-Scale Knowledge Base Population

IBM/cc-dbp European Semantic Web Conference 2018

Knowledge Base Population (KBP) is the task of building or extending a knowledge base from text, and systems for KBP have grown in capability and scope.

Discovering Implicit Knowledge with Unary Relations

IBM/cc-dbp ACL 2018

State-of-the-art relation extraction approaches are only able to recognize relationships between mentions of entity arguments stated explicitly in the text and typically localized to the same sentence.

Type-Sensitive Knowledge Base Inference Without Explicit Type Supervision

dair-iitd/kbi ACL 2018

State-of-the-art knowledge base completion (KBC) models predict a score for every known or unknown fact via a latent factorization over entity and relation embeddings.

Adversarial Feature Adaptation for Cross-lingual Relation Classification

zoubowei/feature_adaptation4RC COLING 2018

In this paper, we come up with a feature adaptation approach for cross-lingual relation classification, which employs a generative adversarial network (GAN) to transfer feature representations from one language with rich annotated data to another language with scarce annotated data.

Improving Named Entity Recognition by Jointly Learning to Disambiguate Morphological Tags

onurgu/joint-ner-and-md-tagger COLING 2018

In this work, we propose a model which alleviates the need for such disambiguators by jointly learning NER and MD taggers in languages for which one can provide a list of candidate morphological analyses.

The INCEpTION Platform: Machine-Assisted and Knowledge-Oriented Interactive Annotation

inception-project/inception COLING 2018

We introduce INCEpTION, a new annotation platform for tasks including interactive and semantic annotation (e. g., concept linking, fact linking, knowledge base population, semantic frame annotation).

Who Sides with Whom? Towards Computational Construction of Discourse Networks for Political Debates

mardy-spp/mardy_acl2019 ACL 2019

Understanding the structures of political debates (which actors make what claims) is essential for understanding democratic political decision making.