Search Results for author: Bingfeng Luo

Found 8 papers, 2 papers with code

Make Templates Smarter: A Template Based Data2Text System Powered by Text Stitch Model

no code implementations Findings of the Association for Computational Linguistics 2020 Bingfeng Luo, Zuo Bai, Kunfeng Lai, Jianping Shen

In addition, it reduces human involvement in template design by using a text stitch model to automatically stitch adjacent template units, which is a step that usually requires careful template design and limits template reusability.

Diversity

NASE: Learning Knowledge Graph Embedding for Link Prediction via Neural Architecture Search

1 code implementation18 Aug 2020 Xiaoyu Kou, Bingfeng Luo, Huang Hu, Yan Zhang

While various forms of models are proposed for the link prediction task, most of them are designed based on a few known relation patterns in several well-known datasets.

Knowledge Graph Embedding Link Prediction +2

Integrating Relation Constraints with Neural Relation Extractors

1 code implementation26 Nov 2019 Yuan Ye, Yansong Feng, Bingfeng Luo, Yuxuan Lai, Dongyan Zhao

However, such models often make predictions for each entity pair individually, thus often fail to solve the inconsistency among different predictions, which can be characterized by discrete relation constraints.

Relation Relation Extraction

Encoding Implicit Relation Requirements for Relation Extraction: A Joint Inference Approach

no code implementations9 Nov 2018 Li-Wei Chen, Yansong Feng, Songfang Huang, Bingfeng Luo, Dongyan Zhao

Relation extraction is the task of identifying predefined relationship between entities, and plays an essential role in information extraction, knowledge base construction, question answering and so on.

Question Answering Relation +1

Marrying up Regular Expressions with Neural Networks: A Case Study for Spoken Language Understanding

no code implementations ACL 2018 Bingfeng Luo, Yansong Feng, Zheng Wang, Songfang Huang, Rui Yan, Dongyan Zhao

The success of many natural language processing (NLP) tasks is bound by the number and quality of annotated data, but there is often a shortage of such training data.

Intent Detection slot-filling +2

Learning to Predict Charges for Criminal Cases with Legal Basis

no code implementations EMNLP 2017 Bingfeng Luo, Yansong Feng, Jianbo Xu, Xiang Zhang, Dongyan Zhao

The charge prediction task is to determine appropriate charges for a given case, which is helpful for legal assistant systems where the user input is fact description.

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