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ACL
2010
9 years 9 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
ACL
2015
4 years 7 months ago
Improving Named Entity Recognition in Tweets via Detecting Non-Standard Words
Most previous work of text normalization on informal text made a strong assumption that the system has already known which tokens are non-standard words (NSW) and thus need normal...
Chen Li, Yang Liu
EMNLP
2010
9 years 9 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
11 years 17 days 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
10 years 6 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-...
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