How to extract entities from text using existing ontologies?
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I am working on a entity extraction task and I am using Stanford CoreNLP NER. Here, I want to detect entities of type "Animal", "Building", "Imagery", etc., which are not covered in Stanford CoreNLP entity extraction method. Also, I want to detect organization entities which are not included in CoreNLP entity model. I have the data about the organizations with me.
How can I do this?
nlp text-mining named-entity-recognition stanford-nlp
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
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bumped to the homepage by Community♦ 6 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
add a comment |
$begingroup$
I am working on a entity extraction task and I am using Stanford CoreNLP NER. Here, I want to detect entities of type "Animal", "Building", "Imagery", etc., which are not covered in Stanford CoreNLP entity extraction method. Also, I want to detect organization entities which are not included in CoreNLP entity model. I have the data about the organizations with me.
How can I do this?
nlp text-mining named-entity-recognition stanford-nlp
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
$endgroup$
bumped to the homepage by Community♦ 6 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
Welcome to the site! See this question.
$endgroup$
– Emre
Mar 27 '18 at 0:18
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Thanks. This works well but suffers from a problem. As this is a dictionary based NER, it does not do the entity disambiguation. For eg, buffalo city can be recognized as the animal buffalo. Currently, I am looking for entity disambiguation techniques.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:07
add a comment |
$begingroup$
I am working on a entity extraction task and I am using Stanford CoreNLP NER. Here, I want to detect entities of type "Animal", "Building", "Imagery", etc., which are not covered in Stanford CoreNLP entity extraction method. Also, I want to detect organization entities which are not included in CoreNLP entity model. I have the data about the organizations with me.
How can I do this?
nlp text-mining named-entity-recognition stanford-nlp
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
$endgroup$
I am working on a entity extraction task and I am using Stanford CoreNLP NER. Here, I want to detect entities of type "Animal", "Building", "Imagery", etc., which are not covered in Stanford CoreNLP entity extraction method. Also, I want to detect organization entities which are not included in CoreNLP entity model. I have the data about the organizations with me.
How can I do this?
nlp text-mining named-entity-recognition stanford-nlp
nlp text-mining named-entity-recognition stanford-nlp
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
asked Mar 26 '18 at 23:29
Swastik RoySwastik Roy
61
61
bumped to the homepage by Community♦ 6 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
bumped to the homepage by Community♦ 6 mins ago
This question has answers that may be good or bad; the system has marked it active so that they can be reviewed.
$begingroup$
Welcome to the site! See this question.
$endgroup$
– Emre
Mar 27 '18 at 0:18
$begingroup$
Thanks. This works well but suffers from a problem. As this is a dictionary based NER, it does not do the entity disambiguation. For eg, buffalo city can be recognized as the animal buffalo. Currently, I am looking for entity disambiguation techniques.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:07
add a comment |
$begingroup$
Welcome to the site! See this question.
$endgroup$
– Emre
Mar 27 '18 at 0:18
$begingroup$
Thanks. This works well but suffers from a problem. As this is a dictionary based NER, it does not do the entity disambiguation. For eg, buffalo city can be recognized as the animal buffalo. Currently, I am looking for entity disambiguation techniques.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:07
$begingroup$
Welcome to the site! See this question.
$endgroup$
– Emre
Mar 27 '18 at 0:18
$begingroup$
Welcome to the site! See this question.
$endgroup$
– Emre
Mar 27 '18 at 0:18
$begingroup$
Thanks. This works well but suffers from a problem. As this is a dictionary based NER, it does not do the entity disambiguation. For eg, buffalo city can be recognized as the animal buffalo. Currently, I am looking for entity disambiguation techniques.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:07
$begingroup$
Thanks. This works well but suffers from a problem. As this is a dictionary based NER, it does not do the entity disambiguation. For eg, buffalo city can be recognized as the animal buffalo. Currently, I am looking for entity disambiguation techniques.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:07
add a comment |
1 Answer
1
active
oldest
votes
$begingroup$
There are multiple ways to extract NER. Primarily, based on the construction of statements NER was extracted with the use of POS tags. But overtime with the change of how information was being conveyed, there has been a migration from traditional methods to learning methods. Currently, take a look at sequence to sequence tagging for NER detection. If you have the appropriate dataset, you have the capability to extract anything you consider as NER.
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
$endgroup$
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
add a comment |
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1 Answer
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1 Answer
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$begingroup$
There are multiple ways to extract NER. Primarily, based on the construction of statements NER was extracted with the use of POS tags. But overtime with the change of how information was being conveyed, there has been a migration from traditional methods to learning methods. Currently, take a look at sequence to sequence tagging for NER detection. If you have the appropriate dataset, you have the capability to extract anything you consider as NER.
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
$endgroup$
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
add a comment |
$begingroup$
There are multiple ways to extract NER. Primarily, based on the construction of statements NER was extracted with the use of POS tags. But overtime with the change of how information was being conveyed, there has been a migration from traditional methods to learning methods. Currently, take a look at sequence to sequence tagging for NER detection. If you have the appropriate dataset, you have the capability to extract anything you consider as NER.
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
$endgroup$
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
add a comment |
$begingroup$
There are multiple ways to extract NER. Primarily, based on the construction of statements NER was extracted with the use of POS tags. But overtime with the change of how information was being conveyed, there has been a migration from traditional methods to learning methods. Currently, take a look at sequence to sequence tagging for NER detection. If you have the appropriate dataset, you have the capability to extract anything you consider as NER.
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
$endgroup$
There are multiple ways to extract NER. Primarily, based on the construction of statements NER was extracted with the use of POS tags. But overtime with the change of how information was being conveyed, there has been a migration from traditional methods to learning methods. Currently, take a look at sequence to sequence tagging for NER detection. If you have the appropriate dataset, you have the capability to extract anything you consider as NER.
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
answered Mar 27 '18 at 6:52
Nischal HpNischal Hp
48829
48829
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
add a comment |
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
$begingroup$
Thank @Nischal, It seems the sequence to sequence tagging needs a lot of training data. Currently, I am focusing on unsupervised or you can say ontology based entity recognition, where I use the entites from public knowledge bases like DbPedia to extract entities.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:09
add a comment |
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$begingroup$
Welcome to the site! See this question.
$endgroup$
– Emre
Mar 27 '18 at 0:18
$begingroup$
Thanks. This works well but suffers from a problem. As this is a dictionary based NER, it does not do the entity disambiguation. For eg, buffalo city can be recognized as the animal buffalo. Currently, I am looking for entity disambiguation techniques.
$endgroup$
– Swastik Roy
Apr 16 '18 at 22:07