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Knowledge Base Population

10 papers with code ยท Natural Language Processing

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PERLEX: A Bilingual Persian-English Gold Dataset for Relation Extraction

13 May 2020

The main motivations of this research stem from a lack of a dataset for relation extraction in the Persian language as well as the necessity of extracting knowledge from the growing big-data in the Persian language for different applications.

KNOWLEDGE BASE POPULATION RELATION EXTRACTION

FarsBase-KBP: A Knowledge Base Population System for the Persian Knowledge Graph

4 May 2020

While most of the knowledge bases already support the English language, there is only one knowledge base for the Persian language, known as FarsBase, which is automatically created via semi-structured web information.

ENTITY LINKING KNOWLEDGE BASE POPULATION RELATION EXTRACTION

Linking Graph Entities with Multiplicity and Provenance

13 Aug 2019

The graph model is versatile, thus, it is capable of handling multiple values for an attribute or a relationship, as well as the provenance descriptions of the values.

ENTITY LINKING INFORMATION RETRIEVAL KNOWLEDGE BASE POPULATION

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

ACL 2019

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

DECISION MAKING KNOWLEDGE BASE POPULATION

Uncovering Probabilistic Implications in Typological Knowledge Bases

ACL 2019

The study of linguistic typology is rooted in the implications we find between linguistic features, such as the fact that languages with object-verb word ordering tend to have postpositions.

KNOWLEDGE BASE POPULATION

Uncovering Probabilistic Implications in Typological Knowledge Bases

ACL 2019

The study of linguistic typology is rooted in the implications we find between linguistic features, such as the fact that languages with object-verb word ordering tend to have post-positions.

KNOWLEDGE BASE POPULATION

Adversarial Training for Satire Detection: Controlling for Confounding Variables

NAACL 2019

We therefore propose a novel model for satire detection with an adversarial component to control for the confounding variable of publication source.

KNOWLEDGE BASE POPULATION

Learning Relational Representations by Analogy using Hierarchical Siamese Networks

NAACL 2019

We address relation extraction as an analogy problem by proposing a novel approach to learn representations of relations expressed by their textual mentions.

ENTITY EMBEDDINGS KNOWLEDGE BASE POPULATION ONE-SHOT LEARNING RELATION EXTRACTION

Adversarial Training for Satire Detection: Controlling for Confounding Variables

NAACL 2019

We therefore propose a novel model for satire detection with an adversarial component to control for the confounding variable of publication source.

KNOWLEDGE BASE POPULATION