7 citations · 27 across the 6 of their papers we have counts for
6 papers
Towards Generalized Open Information Extraction
Bowen Yu, Zhenyu Zhang, Jingyang Li +5
Open Information Extraction (OpenIE) facilitates the open-domain discovery of textual facts. However, the prevailing solutions evaluate OpenIE models on in-domain test sets aside f…
Layout-Aware Information Extraction for Document-Grounded Dialogue: Dataset, Method and Demonstration
Zhenyu Zhang, Bowen Yu, Haiyang Yu +6
Building document-grounded dialogue systems have received growing interest as documents convey a wealth of human knowledge and commonly exist in enterprises. Wherein, how to compre…
A Survey on Neural Open Information Extraction: Current Status and Future Directions
Shaowen Zhou, Bowen Yu, Aixin Sun +5
Open Information Extraction (OpenIE) facilitates domain-independent discovery of relational facts from large corpora. The technique well suits many open-world natural language unde…
Joint Semantics and Data-Driven Path Representation for Knowledge Graph Inference
Guanglin Niu, Bo Li, Yongfei Zhang +4
Inference on a large-scale knowledge graph (KG) is of great importance for KG applications like question answering. The path-based reasoning models can leverage much information ov…
AutoETER: Automated Entity Type Representation for Knowledge Graph Embedding
Guanglin Niu, Bo Li, Yongfei Zhang +2
Recent advances in Knowledge Graph Embedding (KGE) allow for representing entities and relations in continuous vector spaces. Some traditional KGE models leveraging additional type…
Rule-Guided Compositional Representation Learning on Knowledge Graphs
Guanglin Niu, Yongfei Zhang, Bo Li +4
Representation learning on a knowledge graph (KG) is to embed entities and relations of a KG into low-dimensional continuous vector spaces. Early KG embedding methods only pay atte…