Stack Overflow
Stack Overflow

Questions tagged [named-entity-recognition]

Named-entity recognition (NER) (also known as entity identification and entity extraction) is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.

Named-entity recognition (NER) (also known as entity identification and entity extraction) is a subtask of information extraction that seeks to locate and classify atomic elements in text into predefined categories such as the names of persons, organizations, locations, expressions of times, quantities, monetary values, percentages, etc.

Most research on NER systems has been structured as taking an unannotated block of text, such as this one:

Jim bought 300 shares of Acme Corp. in 2006.

And producing an annotated block of text that highlights where the named entities are, such as this one:

<ENAMEX TYPE="PERSON">Jim</ENAMEX>bought<NUMEX TYPE="QUANTITY">300</NUMEX>shares of<ENAMEX TYPE="ORGANIZATION">Acme Corp.</ENAMEX> in <TIMEX TYPE="DATE">2006</TIMEX>.

In this example, the annotations are marked using XML ENAMEX elements, following the format developed for the Message Understanding Conference in the 1990s.

State-of-the-art NER systems for English produce near-human performance. For example, the best system entering MUC-7 scored 93.39% of F-measure while human annotators scored 97.60% and 96.95%.

Source:http://en.wikipedia.org/wiki/Named-entity_recognition

1456 questions
17
votes
1 answer

How to create a good NER training model in OpenNLP?

I just have started with OpenNLP. I need to create a simple training model to recognize name entities. Reading the doc here https://opennlp.apache.org/docs/1.8.0/apidocs/opennlp-tools/opennlp/tools/namefind I see this simple text to train the…
Dail
  • 4,622
  • 16
  • 74
  • 109
16
votes
1 answer

How to create NER pipeline with multiple models in Spacy

I am trying to train new entities for spacy NER. I tried adding my new entity to existing spacy 'en' model. However, this affected the prediction model for both 'en' and my new entity. I, therefore, created a blank model and trained the entity…
Suvin K S
  • 229
  • 2
  • 8
16
votes
1 answer

Understanding Spacy's Scorer Output

I'm evaluating a custom NER model that I built using Spacy. I'm evaluating the training sets using Spacy's Scorer class. def Eval(examples): # test the saved model print("Loading from", './model6/') ner_model =…
Evan Lalo
  • 1,209
  • 1
  • 14
  • 34
15
votes
3 answers

Replace entity with its label in SpaCy

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…
eng2019
  • 953
  • 10
  • 26
15
votes
1 answer

NLP : Is Gazetteer a cheat

In NLP there is a concept of Gazetteer which can be quite useful for creating annotations. As far as i understand, A gazetteer consists of a set of lists containing names of entities such as cities, organisations, days of the week, etc. These lists…
AbtPst
  • 7,778
  • 17
  • 91
  • 172
15
votes
2 answers

Extracting multi word named entities using CoreNLP

I'm using CoreNLP for named entity extraction and have run into a bit of an issue. The issue is that whenever a named entity is composed of more than one token, such as "Han Solo", the annotator does not return "Han Solo" as a single named entity,…
MarkB
  • 1,783
  • 2
  • 17
  • 32
15
votes
4 answers

Sentiment Analysis of Entity (Entity-level Sentiment Analysis)

I've been working on document level sentiment analysis since past 1 year. Document level sentiment analysis provides the sentiment of the complete document. For example - The text "Nokia is good but vodafone sucks big time" would have a negative…
Jasneet
  • 302
  • 4
  • 14
14
votes
8 answers

Strategies for recognizing proper nouns in NLP

I'm interested in learning more about Natural Language Processing (NLP) and am curious if there are currently any strategies for recognizing proper nouns in a text that aren't based on dictionary recognition? Also, could anyone explain or link to…
VirtuosiMedia
  • 52,016
  • 21
  • 93
  • 140
14
votes
1 answer

How do I use python interface of Stanford NER(named entity recogniser)?

I want to use Stanford NER in python using pyner library. Here is one basic code snippet. import ner tagger = ner.HttpNER(host='localhost', port=80) tagger.get_entities("University of California is located in California, United States") When I run…
Vinit Gaikwad
  • 329
  • 9
  • 21
13
votes
1 answer

How to use a CRF layer in Tensorflow 2 (using tfa.text)?

model= Sequential() model.add(keras.layers.Embedding(vocab_size,output_dim=100,input_length=input_len,weights=[embedding_matrix],trainable=False)) model.add(keras.layers.Bidirectional(keras.layers.LSTM(512,…
Ankush Panwar
  • 131
  • 4
13
votes
6 answers

is there a way with spaCy's NER to calculate metrics per entity type?

is there a way in the NER model in spaCy to extract the metrics (precision, recall, f1 score) per entity type? Something that will look like this: precision recall f1-score support B-LOC 0.810 0.784 0.797 1084 …
ln pi
  • 131
  • 1
  • 1
  • 4
12
votes
2 answers

Named entity recognition in Spacy

I am trying to find Named entities for a sentence as below import spacy.lang.en parser = spacy.lang.en.English() ParsedSentence = parser(u"Alphabet is a new startup in China") for Entity in ParsedSentence.ents: print (Entity.label,…
shan
  • 467
  • 4
  • 9
  • 20
11
votes
3 answers

How to reconstruct text entities with Hugging Face's transformers pipelines without IOB tags?

I've been looking to use Hugging Face's Pipelines for NER (named entity recognition). However, it is returning the entity labels in inside-outside-beginning (IOB) format but without the IOB labels. So I'm not able to map the output of the pipeline…
Union find
  • 7,759
  • 13
  • 60
  • 111
11
votes
2 answers

Case-sensitive entity recognition

I have keywords that are all stored in lower case, e.g. "discount nike shoes", that I am trying to perform entity extraction on. The issue I've run into is that spaCy seems to be case sensitive when it comes to NER. Mind you , I don't think that…
Emma Jean
  • 507
  • 3
  • 12
11
votes
2 answers

What's the ideal way to include dictionaries (gazetteer) in spaCy to improve NER?

I'm currently working on replacing a system based on nltk entity extraction combined with regexp matching where I have several named entity dictionaries. The dictionary entities are both of common type (PERSON (employees) etc.) as well as custom…
Einar Magnússon
  • 141
  • 1
  • 4
1
2
3
…
96 97