Prompt-Learning for Fine-Grained Entity Typing (original) (raw)

Fine-Grained Entity Type Classification by Jointly Learning Representations and Label Embeddings

Ashish Anand

Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers

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Description-Based Zero-shot Fine-Grained Entity Typing

Rasha Obeidat

Proceedings of the 2019 Conference of the North, 2019

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Generative Entity Typing with Curriculum Learning

Jingyue Huang

2022

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Learning with Noise: Improving Distantly-Supervised Fine-grained Entity Typing via Automatic Relabeling

Muhua Zhu

Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence, 2020

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Do Judge an Entity by Its Name! Entity Typing Using Language Models

Russa Biswas

The Semantic Web: ESWC 2021 Satellite Events, 2021

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Fine-grained entity type classification using GRU with self-attention

Anuraj Mohan

International Journal of Information Technology, 2020

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Knowledgeable Prompt-tuning: Incorporating Knowledge into Prompt Verbalizer for Text Classification

Shengding Hu

2021

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Improving Language Model Predictions via Prompts Enriched with Knowledge Graphs

Ryan Brate

Zenodo (CERN European Organization for Nuclear Research), 2023

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Zero-shot Entity and Tweet Characterization with Designed Conditional Prompts and Contexts

Tushar Mohan

ArXiv, 2022

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Context-Dependent Fine-Grained Entity Type Tagging

Jessica Kirchner

2014

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Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing

Mingtao Dong

Cornell University - arXiv, 2022

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Few-NERD: A Few-shot Named Entity Recognition Dataset

Jhonny Muñoz

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), 2021

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Few-Shot Named Entity Recognition: An Empirical Baseline Study

Damien Jose

2021

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Making Pre-trained Language Models End-to-end Few-shot Learners with Contrastive Prompt Tuning

Ziyun Xu

Cornell University - arXiv, 2022

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EntEval: A Holistic Evaluation Benchmark for Entity Representations

ZEWEI CHU

Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)

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Fine and Ultra-Fine Entity Type Embeddings for Question Answering

Jennifer Sleeman

2020

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SANE: System for Fine Grained Named Entity Typing on Textual Data

Apoorve Tomer

Proceedings of the 26th International Conference on World Wide Web Companion, 2017

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Automatic Entity Recognition and Typing in Massive Text Corpora

Ahmed El-Kishky

2020

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Fine grained classification of named entities

Claudio Giuliano

Proceedings of the 19th international conference on Computational linguistics -, 2002

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Automatic Entity Recognition and Typing in Massive Text Data

Ahmed El-Kishky

Proceedings of the 2016 International Conference on Management of Data - SIGMOD '16, 2016

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Assessing the challenge of fine-grained named entity recognition and classification

Anette Frank

2010

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Generating Training Data with Language Models: Towards Zero-Shot Language Understanding

Jiawei Han

arXiv (Cornell University), 2022

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Few-Shot Named Entity Recognition: A Comprehensive Study

krishan subudhi

ArXiv, 2020

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Fine-Grained Named Entity Recognition using ELMo and Wikidata

Alfredo Gemma

ArXiv, 2019

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SANE 2.0: System for fine grained named entity typing on textual data

Anurag Lal

Engineering Applications of Artificial Intelligence, 2019

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Finetuned Language Models Are Zero-Shot Learners

Brian Lester

2021

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How Can Cross-lingual Knowledge Contribute Better to Fine-Grained Entity Typing?

Tiansi Dong

Findings of the Association for Computational Linguistics: ACL 2022

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Accelerating the annotation of sparse named entities by dynamic sentence selection

Junichi Tsujii

BMC Bioinformatics, 2008

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Large Language Models Are Human-Level Prompt Engineers

Andrei Muresanu

Cornell University - arXiv, 2022

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Few-shot Instruction Prompts for Pretrained Language Models to Detect Social Biases

Rafal Kocielnik

ArXiv, 2021

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Entity Type Recognition Using an Ensemble of Distributional Semantic Models to Enhance Query Understanding

Trey Grainger

2016 IEEE 40th Annual Computer Software and Applications Conference (COMPSAC), 2016

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Fine-Grained Named Entity Recognition Using Conditional Random Fields for Question Answering

Changki Lee

Information Retrieval Technology, 2006

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Precog-LTRC-IIITH at GermEval 2021: Ensembling Pre-Trained Language Models with Feature Engineering

T.H Arjun

2021

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Regularization for Long Named Entity Recognition

Jaewo Kang

2021

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Deciphering Political Entity Sentiment in News with Large Language Models: Zero-Shot and Few-Shot Strategies

Alapan Kuila

arXiv (Cornell University), 2024

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