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» Hierarchical Joint Learning: Improving Joint Parsing and Nam...
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ACL
2010
13 years 1 months ago
Hierarchical Joint Learning: Improving Joint Parsing and Named Entity Recognition with Non-Jointly Labeled Data
One of the main obstacles to producing high quality joint models is the lack of jointly annotated data. Joint modeling of multiple natural language processing tasks outperforms si...
Jenny Rose Finkel, Christopher D. Manning
EMNLP
2010
13 years 1 months ago
Joint Training and Decoding Using Virtual Nodes for Cascaded Segmentation and Tagging Tasks
Many sequence labeling tasks in NLP require solving a cascade of segmentation and tagging subtasks, such as Chinese POS tagging, named entity recognition, and so on. Traditional p...
Xian Qian, Qi Zhang, Yaqian Zhou, Xuanjing Huang, ...
ICML
2008
IEEE
14 years 4 months ago
A unified architecture for natural language processing: deep neural networks with multitask learning
We describe a single convolutional neural network architecture that, given a sentence, outputs a host of language processing predictions: part-of-speech tags, chunks, named entity...
Ronan Collobert, Jason Weston
WWW
2009
ACM
13 years 10 months ago
StatSnowball: a statistical approach to extracting entity relationships
Traditional relation extraction methods require pre-specified relations and relation-specific human-tagged examples. Bootstrapping systems significantly reduce the number of tr...
Jun Zhu, Zaiqing Nie, Xiaojiang Liu, Bo Zhang, Ji-...