[PDF] Top 20 Multi Task Learning for Chemical Named Entity Recognition with Chemical Compound Paraphrasing
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Multi Task Learning for Chemical Named Entity Recognition with Chemical Compound Paraphrasing
... Named Entity Recognition (NER) is one of the important basic technologies for Natural Lan- guage Processing (NLP) such as Information Extraction and Entity ...shared task (Sang et ... See full document
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Multi grained Named Entity Recognition
... NER Task. The proposed MGNER is very suitable for detecting nested named entities since every possible entity will be examined and ...for learning feature represen- tations; 6) Ju et ... See full document
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Multi Criteria based Active Learning for Named Entity Recognition
... supervised learning in which the entire corpus are labeled manually, active learning is to select the most useful example for labe ling and add the labeled example to training set to retrain ... See full document
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Transfer Learning in Biomedical Named Entity Recognition: An Evaluation of BERT in the PharmaCoNER task
... PharmaCoNER task still yields competitive per- ...of chemical and protein men- tions sharing the same name in English and Span- ish in biomedical ... See full document
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A Multi task Approach for Named Entity Recognition in Social Media Data
... Named Entity Recognition (NER) aims at iden- tifying different types of entities, such as people names, companies, location, ...2009). Learning Named En- tities (NEs) from social media ... See full document
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Joint Learning of Named Entity Recognition and Entity Linking
... Named entity recognition (NER) and entity linking (EL) are two fundamentally related tasks, since in order to perform EL, first the mentions to entities have to be ...most entity ... See full document
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Deep Active Learning for Named Entity Recognition
... The learning process consists of multiple rounds: At the beginning of each round, the active learn- ing algorithm chooses sentences to be annotated up to the predefined ...active learning strategies suit ... See full document
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Multi-Engine Approach for Named Entity Recognition in Bengali
... Named Entity Recognition (NER) is an important tool in almost all Natural Language Processing (NLP) application areas including machine translation, question answering, information retrieval, ... See full document
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A Neural Multi-Task Learning Framework to Jointly Model Medical Named Entity Recognition and Normalization
... medical named entity recognition model to extract entity names first, then run a medical named entity normaliza- tion model to link extracted names to a controlled vocab- ulary ... See full document
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A Multi task Learning Approach to Adapting Bilingual Word Embeddings for Cross lingual Named Entity Recognition
... name-entity recognition (NER) system in a language with no labeled ...proposed multi-task model jointly trains bilingual word embeddings while optimizing a NER ... See full document
6
Chemical named entities recognition: a review on approaches and applications
... of chemical compounds in the texts is useful for many rea- sons, including mapping entities to corresponding struc- tures to find relationships between ...this entity class, such as their activ- ities, ... See full document
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Attribute based Chinese Named Entity Recognition and Disambiguation
... KBP task and WePS task are public evalua- tion campaigns for entity disambiguation, providing annotated datasets for training and ...an entity disambiguation system based on attribute extrac- ... See full document
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Maximum Entropy Approach based Named Entity Recognition in Punjabi Language
... etc. Named Entity Recognition (NER) is the task of identifying and classifying the Named Entities into predefine categories such as person, organization, location, etc in the ...(IE) ... See full document
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Stopping Criteria for Active Learning of Named Entity Recognition
... Table 2: Performance estimation. LOO and Lewis overestimate true F by 6% and 13%, respectively. We find that both methods overestimate preci- sion and recall by a large margin. We also note that the peak in performance ... See full document
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Named Entity Recognition Using Machine Learning Approaches
... Shipra Dingare, MalvinaNissim Jenny Finkel, Christopher Manning and Claire Grover [3], the author presents a Named Entity Recognition based on maximum entropy system for extracting entities present ... See full document
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Bundschus, Markus (2010): From Text to Knowledge: Bridging the Gap with Probabilistic Graphical Models. Dissertation, LMU München: Fakultät für Mathematik, Informatik und Statistik
... classification task, Text2SemRel’s RE algorithm is based on sequence labeling, thus we use an algorithm that models se- ...an entity of the city class and an entity of the act class (see Section ... See full document
170
Named Entity Recognition for Novel Types by Transfer Learning
... transfer learning to deal with NER data sets with different label ...target task affects the source task, and demonstrated that decod- ing for transfer is better than no transfer, and joint decoding ... See full document
7
Learning to recognise named entities in tweets by exploiting weakly labelled data
... machine learning al- gorithm, which will then discriminate between various semantic types based on those ...machine learning-based approach with entity linking methods which exploit knowledge bases ... See full document
11
Chinese Name Disambiguation Based on Adaptive Clustering with the Attribute Features
... be named as char- acter attribute features, including 12-dimension, respectively, the person’s name (rm), place (dm), organization(jg), career(zy), position(zw), award- s (ry), gender (xb), nation(mz), education ... See full document
6
Named Entity Recognition in Estonian
... Papers on NER for English language commonly use publicly available named entity tagged corpora for system development and evaluation (Tjong Kim Sang and De Meulder, 2003; Chinchor, 1998). As no such ... See full document
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