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Found 9 papers, 3 papers with code
How Can Cross-lingual Knowledge Contribute Better to Fine-Grained Entity Typing?
Cross-lingual Entity Typing (CLET) aims at improving the quality of entity type prediction by transferring semantic knowledge learned from rich-resourced languages to low-resourced languages.
Sphere Neural-Networks for Rational Reasoning
SphNN is the first neural model that can determine the validity of long-chained syllogistic reasoning in one epoch by constructing sphere configurations as Euler diagrams, with the worst computational complexity of O(N^2).
Word Sense Disambiguation as a Game of Neurosymbolic Darts
The core of our methodology is a neurosymbolic sense embedding, in terms of a configuration of nested balls in n-dimensional space.
Interpretable and Low-Resource Entity Matching via Decoupling Feature Learning from Decision Making
Using a set of comparison features and a limited amount of annotated data, KAT Induction learns an efficient decision tree that can be interpreted by generating entity matching rules whose structure is advocated by domain experts.
Learning Syllogism with Euler Neural-Networks
In contrast to traditional neural network, ENN can precisely represent all 24 different structures of Syllogism.
Fine-Grained Entity Typing via Hierarchical Multi Graph Convolutional Networks
This paper addresses the problem of inferring the fine-grained type of an entity from a knowledge base.
Encoding Category Trees Into Word-Embeddings Using Geometric Approach
Experiment results also show that $n$-ball embeddings demonstrate surprisingly good performance in validating the category of unknown word.
Joint Representation Learning of Cross-lingual Words and Entities via Attentive Distant Supervision
Joint representation learning of words and entities benefits many NLP tasks, but has not been well explored in cross-lingual settings.
Attributed and Predictive Entity Embedding for Fine-Grained Entity Typing in Knowledge Bases
Fine-grained entity typing aims at identifying the semantic type of an entity in KB.
