We design a set of word frequency-based reliability signals to indicate the quality of each word embedding. Guided by the reliability signals, the model is able ...

To incorpo- rate the character-level representation and context- only features, we design new gating mechanisms to mix them with the word embedding and en-.

In this paper, we propose a novel reliability-aware name tagging model to tackle this issue. We design a set of word frequency-based reliability signals to ...

(2019) Reliability-aware Dynamic Feature Composition for Name Tagging. Proceedings of The 57th Annual Meeting of the Association for Computational Linguistics.

Inspired by the work of Ying et al. [8] which uses a reliability signal to dynamically select features from word-level embedding and character-level embedding ...

Reliability-aware Dynamic Feature Composition for Name Tagging. Ying Lin ... Task. Tagging Named Entity Recognition Information Extraction Biomedical ...

Code for "Reliability-aware Dynamic Feature Composition for Name Tagging" (ACL2019). Python 37 5 · mlmt mlmt Public. Code for the paper "A Multi-lingual ...

Reliability-aware Dynamic Feature Composition for Name Tagging. Word embeddings are widely used on a variety of tasks and can substantially improve the ...

Current supervised name tagging approaches are inadequate for most low-resource languages due to the lack of annotated data and actionable linguistic knowledge.

Reliability-aware dynamic feature composition can be applied to cases where the quality of input features are not consistent. For example, in some sentiment ...