CLUENER2020
CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition
view repo
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for name entity recognition in Chinese. CLUENER2020 contains 10 categories. Apart from common labels like person, organization and location, it contains more diverse categories. It is more challenging than current other Chinese NER datasets and could better reflect real-world applications. For comparison, we implement several state-of-the-art baselines as sequence labelling tasks and report human performance, as well as its analysis. To facilitate future work on fine-grained NER for Chinese, we release our dataset, baselines and leader-board.
READ FULL TEXT
In this paper, we introduce the NER dataset from CLUE organization
(CLUE...
read it
Fine-grained entity typing is a challenging task with wide applications....
read it
Named Entity Recognition (NER) is an essential precursor task for many
n...
read it
Empirical methods in geoparsing have thus far lacked a standard evaluati...
read it
Chinese text recognition is more challenging than Latin text due to the ...
read it
With the recent progress in machine learning, boosted by techniques such...
read it
Suggestion mining tasks are often semantically complex and lack sophisti...
read it
CLUENER2020 中文细粒度命名实体识别 Fine Grained Named Entity Recognition
Comments
There are no comments yet.