Entity Linking
277 papers with code • 27 benchmarks • 44 datasets
Assigning a unique identity to entities (such as famous individuals, locations, or companies) mentioned in text (Source: Wikipedia).
Libraries
Use these libraries to find Entity Linking models and implementationsMost implemented papers
Named Entity Recognition with Bidirectional LSTM-CNNs
Named entity recognition is a challenging task that has traditionally required large amounts of knowledge in the form of feature engineering and lexicons to achieve high performance.
Zero-Shot Entity Linking by Reading Entity Descriptions
First, we show that strong reading comprehension models pre-trained on large unlabeled data can be used to generalize to unseen entities.
Scalable Zero-shot Entity Linking with Dense Entity Retrieval
This paper introduces a conceptually simple, scalable, and highly effective BERT-based entity linking model, along with an extensive evaluation of its accuracy-speed trade-off.
KILT: a Benchmark for Knowledge Intensive Language Tasks
We test both task-specific and general baselines, evaluating downstream performance in addition to the ability of the models to provide provenance.
Efficient One-Pass End-to-End Entity Linking for Questions
We present ELQ, a fast end-to-end entity linking model for questions, which uses a biencoder to jointly perform mention detection and linking in one pass.
Visual FUDGE: Form Understanding via Dynamic Graph Editing
FUDGE edits the graph structure by combining text segments (graph vertices) and pruning edges in an iterative fashion to obtain the final text entities and relationships.
WikiDiverse: A Multimodal Entity Linking Dataset with Diversified Contextual Topics and Entity Types
In this paper, we present WikiDiverse, a high-quality human-annotated MEL dataset with diversified contextual topics and entity types from Wikinews, which uses Wikipedia as the corresponding knowledge base.
LayoutLMv3: Pre-training for Document AI with Unified Text and Image Masking
In this paper, we propose \textbf{LayoutLMv3} to pre-train multimodal Transformers for Document AI with unified text and image masking.
ReFinED: An Efficient Zero-shot-capable Approach to End-to-End Entity Linking
The model is capable of generalising to large-scale knowledge bases such as Wikidata (which has 15 times more entities than Wikipedia) and of zero-shot entity linking.
Improving Entity Disambiguation by Reasoning over a Knowledge Base
Recent work in entity disambiguation (ED) has typically neglected structured knowledge base (KB) facts, and instead relied on a limited subset of KB information, such as entity descriptions or types.