Papers with entity linking systems
Unified Examination of Entity Linking in Absence of Candidate Sets (2024.naacl-short)
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| Challenge: | Entity linking systems depend on candidate sets for their performance, but a comprehensive comparative analysis of these systems is lacking. |
| Approach: | They propose a black-box benchmark and a method to evaluate all state-of-the-art entity linking methods. |
| Outcome: | The proposed approach reduces the inference time and memory footprint of some models. |
entity-linkings: A Unified Library for Entity Linking (2026.eacl-demo)
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| Challenge: | Entity linking (EL) is the task of mapping named entities in text to canonical entries in a knowledge base. |
| Approach: | They propose a unified library for using and developing entity linking systems . a strong emphasis is placed on usability, making it highly extensible . |
| Outcome: | a new library aims to disambiguate named entities in text by mapping them to canonical entries in a knowledge base. |
Systematic Study of Long Tail Phenomena in Entity Linking (C18-1)
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| Challenge: | Existing systems for entity linking are based on frequent 'head' cases, while performance drops when moving towards rare 'long tail' entities. |
| Approach: | They propose to use a long tail to investigate the properties of entity linking datasets. |
| Outcome: | The proposed systems overfit to popular/frequent and non-ambiguous cases and find the most difficult cases among the infrequent candidates of ambiguous forms. |
Effective Use of Context in Noisy Entity Linking (D18-1)
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| Challenge: | Effectively using an entity mention's context to disambiguate it is the crux of the entity linking task. |
| Approach: | They propose to use convolutional neural networks to extract cues from context to effectively disambiguate between closely related concepts. |
| Outcome: | The proposed model outperforms previous work on the WikilinksNED test set by 2.8% absolute. |
Boosting Entity Linking Performance by Leveraging Unlabeled Documents (P19-1)
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| Challenge: | a new approach to entity linking relies on unlabeled documents and Wikipedia . a supervised approach uses only natural information, such as unlabed documents . |
| Approach: | They propose a method which exploits only naturally occurring information . they construct a high recall list of candidate entities for each mention in an unlabeled document . |
| Outcome: | The proposed model outperforms fully-supervised state-of-the-art systems on standard test sets. |
OpenEL: An Annotated Corpus for Entity Linking and Discourse in Open Domain Dialogue (2022.lrec-1)
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| Challenge: | Named entity recognition (NER), named entity linking and discourse modeling are crucial aspects of natural language understanding for open domain dialogue systems. |
| Approach: | They present an annotated multi-domain corpus for linking entities in open-domain dialogue . they use dialogue context and anaphora resolution to assess the effectiveness of the task . |
| Outcome: | The OpenEL corpus is an annotated multi-domain corpus for linking entities in open-domain dialogue . the system Flair + BLINK has the best performance with a 0.65 F1 score . |
Entity Linking via Explicit Mention-Mention Coreference Modeling (2022.naacl-main)
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| Challenge: | Using a learning approach for entity mentions is a key component of modern entity linking systems for both candidate generation and making linking predictions. |
| Approach: | They propose a training approach that builds minimum spanning arborescences over mentions and entities to explicitly model mention coreference relationships. |
| Outcome: | The proposed approach improves candidate generation recall and link accuracy on the biomedical dataset and on MedMentions, setting a new SOTA result in linking accuracy. |