6 citations · 8 across the 3 of their papers we have counts for
7 papers
To be Closer: Learning to Link up Aspects with Opinions
Yuxiang Zhou, Lejian Liao, Yang Gao +2
Dependency parse trees are helpful for discovering the opinion words in aspect-based sentiment analysis (ABSA). However, the trees obtained from off-the-shelf dependency parsers ar…
Better Feature Integration for Named Entity Recognition
Lu Xu, Zhanming Jie, Wei Lu +1
It has been shown that named entity recognition (NER) could benefit from incorporating the long-distance structured information captured by dependency trees. We believe this is bec…
ENT-DESC: Entity Description Generation by Exploring Knowledge Graph
Liying Cheng, Dekun Wu, Lidong Bing +4
Previous works on knowledge-to-text generation take as input a few RDF triples or key-value pairs conveying the knowledge of some entities to generate a natural language descriptio…
Dependency-Guided LSTM-CRF for Named Entity Recognition
Zhanming Jie, Wei Lu
Dependency tree structures capture long-distance and syntactic relationships between words in a sentence. The syntactic relations (e.g., nominal subject, object) can potentially in…
Efficient Dependency-Guided Named Entity Recognition
Zhanming Jie, Aldrian Obaja Muis, Wei Lu
Named entity recognition (NER), which focuses on the extraction of semantically meaningful named entities and their semantic classes from text, serves as an indispensable component…
Dependency-based Hybrid Trees for Semantic Parsing
Zhanming Jie, Wei Lu
We propose a novel dependency-based hybrid tree model for semantic parsing, which converts natural language utterance into machine interpretable meaning representations. Unlike pre…