Papers with Entity typing

4 papers
EnCore: Fine-Grained Entity Typing by Pre-Training Entity Encoders on Coreference Chains (2024.eacl-long)

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Challenge: Entity typing is the task of assigning semantic types to entities mentioned in text.
Approach: They propose to pre-train an entity encoder such that embeddings of coreferring entities are more similar to each other.
Outcome: The proposed method improves state-of-the-art on fine-grained entity typing and entity extraction.
Put It Back: Entity Typing with Language Model Enhancement (D18-1)

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Challenge: Existing Entity typing models suffer from noisy labels due to distant supervision .
Approach: They propose to enhance existing entity typing models with language model enhancement to measure compatibility between context sentences and labels.
Outcome: The proposed model significantly outperforms the state-of-the-art model on benchmark datasets and is available on github.
Generative Entity Typing with Curriculum Learning (2022.emnlp-main)

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Challenge: Entity typing fails to assign an entity to the types beyond the predefined type set.
Approach: They propose a generative entity typing paradigm that assigns types to entities . traditional classification-based approaches fail to assign entities to the types beyond the predefined set . they employ curriculum learning to train the model on heterogeneous data .
Outcome: The proposed model outperforms the state-of-the-art model on heterogeneous training data.
Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing (2022.emnlp-main)

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Challenge: Existing entity typing models are subject to spurious correlations due to shortcuts and biased training.
Approach: They propose a method to augment existing model biases by combining spurious correlations with debiasedcounterparts to improve generalization.
Outcome: The proposed method improves generalization of different entity typing models on the original and debiased test sets.

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