Entity Disambiguation
56 papers with code • 10 benchmarks • 11 datasets
Entity Disambiguation is the task of linking mentions of ambiguous entities to their referent entities in a knowledge base such as Wikipedia.
Source: Leveraging Deep Neural Networks and Knowledge Graphs for Entity Disambiguation
Benchmarks
These leaderboards are used to track progress in Entity Disambiguation
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Datasets
CoNLL
AIDA CoNLL-YAGO
AQUAINT
TAC 2010
Wikidata-Disamb
Latest papers with no code
Entity Disambiguation via Fusion Entity Decoding
Existing generative approaches demonstrate improved accuracy compared to classification approaches under the standardized ZELDA benchmark.
EntGPT: Linking Generative Large Language Models with Knowledge Bases
Overall, the prompting method improves the micro-F_1 score of the original vanilla models by a large margin, on some cases up to 36% and higher, and obtains comparable performance across 10 datasets when compared to existing methods with SFT.
Coherent Entity Disambiguation via Modeling Topic and Categorical Dependency
We propose CoherentED, an ED system equipped with novel designs aimed at enhancing the coherence of entity predictions.
Direct Fact Retrieval from Knowledge Graphs without Entity Linking
There has been a surge of interest in utilizing Knowledge Graphs (KGs) for various natural language processing/understanding tasks.
Polar Ducks and Where to Find Them: Enhancing Entity Linking with Duck Typing and Polar Box Embeddings
Inspired by duck typing in programming languages, we propose to define the type of an entity based on the relations that it has with other entities in a knowledge graph.
Focusing on Context is NICE: Improving Overshadowed Entity Disambiguation
Entity disambiguation (ED) is the task of mapping an ambiguous entity mention to the corresponding entry in a structured knowledge base.
CM3: A Causal Masked Multimodal Model of the Internet
We introduce CM3, a family of causally masked generative models trained over a large corpus of structured multi-modal documents that can contain both text and image tokens.
Global Entity Disambiguation with BERT
We propose a global entity disambiguation (ED) model based on BERT.
Protagonists' Tagger in Literary Domain -- New Datasets and a Method for Person Entity Linkage
We prepared a method for person entity linkage (named entity recognition and disambiguation) and new testing datasets.
Cluster-based Mention Typing for Named Entity Disambiguation
At the named entity disambiguation phase, first the cluster-based types of a given mention are predicted and then, these types are used as features in a ranking model to select the best entity among the candidates.
