Entity Typing

16 papers with code ยท Natural Language Processing

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Latest papers without code

ORB: An Open Reading Benchmark for Comprehensive Evaluation of Machine Reading Comprehension

29 Dec 2019

A lot of diverse reading comprehension datasets have recently been introduced to study various phenomena in natural language, ranging from simple paraphrase matching and entity typing to entity tracking and understanding the implications of the context.

ENTITY TYPING MACHINE READING COMPREHENSION REPRESENTATION LEARNING

Pretrained Encyclopedia: Weakly Supervised Knowledge-Pretrained Language Model

20 Dec 2019

Models trained with our new objective yield significant improvements on the fact completion task.

ENTITY TYPING LANGUAGE MODELLING QUESTION ANSWERING

KEPLER: A Unified Model for Knowledge Embedding and Pre-trained Language Representation

13 Nov 2019

Knowledge embedding (KE) algorithms encode the entities and relations in knowledge graphs into informative embeddings to do knowledge graph completion and provide external knowledge for various NLP applications.

ENTITY EMBEDDINGS ENTITY TYPING KNOWLEDGE GRAPH COMPLETION KNOWLEDGE GRAPH EMBEDDINGS RELATION EXTRACTION

Learning to Few-Shot Learn Across Diverse Natural Language Classification Tasks

10 Nov 2019

Self-supervised pre-training of transformer models has shown enormous success in improving performance on a number of downstream tasks.

ENTITY TYPING FEW-SHOT LEARNING META-LEARNING NATURAL LANGUAGE INFERENCE RELATION EXTRACTION SENTIMENT ANALYSIS TEXT CATEGORIZATION

Comprehensive Multi-Dataset Evaluation of Reading Comprehension

WS 2019

A lot of diverse reading comprehension datasets have recently been introduced to study various phenomena in natural language, ranging from simple paraphrase matching and entity typing to entity tracking and understanding the implications of the context.

ENTITY TYPING READING COMPREHENSION REPRESENTATION LEARNING

Knowledge Enhanced Contextual Word Representations

IJCNLP 2019

Contextual word representations, typically trained on unstructured, unlabeled text, do not contain any explicit grounding to real world entities and are often unable to remember facts about those entities.

ENTITY EMBEDDINGS ENTITY LINKING ENTITY TYPING LANGUAGE MODELLING WORD SENSE DISAMBIGUATION

EntEval: A Holistic Evaluation Benchmark for Entity Representations

IJCNLP 2019

Rich entity representations are useful for a wide class of problems involving entities.

ENTITY DISAMBIGUATION ENTITY TYPING