named-entity-recognition

问题 I'm building my own knowledge base from scratch, using articles online. I am trying to map the entities from my scraped SPO triples (the Subject and potentially the Object) to my own record of entities which consist of listed companies which I scraped from some other website. I've researched most of the libraries, and the method are focused on mapping entities to big knowledge bases like Wikipedia, YAGO, etc., but I'm not really sure how to apply those techniques to my own knowledge base.

问题 I know there are a bunch of questions on this problem and I have read some of those but none of them worked for me. I am trying to build a model with the following architecture: The code is as follows: token_inputs = Input((32,), dtype=tf.int32, name='input_ids') mask_inputs = Input((32,), dtype=tf.int32, name='attention_mask') seg_inputs = Input((32,), dtype=tf.int32, name='token_type_ids') seq_out, _ = bert_model([token_inputs, mask_inputs, seg_inputs]) bd = Bidirectional(LSTM(units=50,

问题 I know there are a bunch of questions on this problem and I have read some of those but none of them worked for me. I am trying to build a model with the following architecture: The code is as follows: token_inputs = Input((32,), dtype=tf.int32, name='input_ids') mask_inputs = Input((32,), dtype=tf.int32, name='attention_mask') seg_inputs = Input((32,), dtype=tf.int32, name='token_type_ids') seq_out, _ = bert_model([token_inputs, mask_inputs, seg_inputs]) bd = Bidirectional(LSTM(units=50,

问题 I have below code in R for extracting person and locations from text: library(rvest) library(NLP) library(openNLP) page = pdf_text("C:/Users/u214738/Documents/NER_Data.pdf") text = as.String(page) sent_annot = Maxent_Sent_Token_Annotator() word_annot = Maxent_Word_Token_Annotator() install.packages("openNLPmodels", repos = "http://datacube.wu.ac.at/src/contrib/", type = "source") install.packages("openNLPmodels.en", repos = "http://datacube.wu.ac.at/", type = "source") install.packages(

问题 While learning the basics of text mining i run into the following problem: I must use named entity annotation to find and locate named entities. However, when found, the tag must be included in the document. So for example: "Hello I am Koen" must result in "Hello I am < PERSON> Koen < /PERSON>. I figured out how to find and label the named entities but I am stuck on getting them in the file in the right way. I've tried comparing if the ent.orth_ is in the file and then replace it with the tag

问题 Can we customize the Named Entity Recognition (NER) model in Azure ML Studio with a separate training dataset? What I want to do is to find out non-English names from a text. (Training dataset includes the set of names that going to use for training) 回答1: Unfortunately, this module's ability to perform NER with a custom set of entities is planned for the future, but not currently available. If you're familiar with Python and willing to put in the extra footwork, you might consider using the

问题 Is there anyway by SpaCy to replace entity detected by SpaCy NER with its label? For example: I am eating an apple while playing with my Apple Macbook. I have trained NER model with SpaCy to detect "FRUITS" entity and the model successfully detects the first "apple" as "FRUITS", but not the second "Apple". I want to do post-processing of my data by replacing each entity with its label, so I want to replace the first "apple" with "FRUITS". The sentence will be " I am eating an FRUITS while

问题 Is there anyway by SpaCy to replace entity detected by SpaCy NER with its label? For example: I am eating an apple while playing with my Apple Macbook. I have trained NER model with SpaCy to detect "FRUITS" entity and the model successfully detects the first "apple" as "FRUITS", but not the second "Apple". I want to do post-processing of my data by replacing each entity with its label, so I want to replace the first "apple" with "FRUITS". The sentence will be " I am eating an FRUITS while

问题 Closed . This question needs to be more focused. It is not currently accepting answers. Want to improve this question? Update the question so it focuses on one problem only by editing this post. Closed 5 days ago . Improve this question I am working on creating ner pipelines for different use-cases. I am planning to use aws for ner pipelines. I have three questions. 1.) Different Options for creating ner pipelines other than aws. 2.) is there any cost-efficient approach other than aws one to

来源： https://stackoverflow.com/questions/56384231/case-sensitive-entity-recognition