Extracting the person names in the named entity recognition in NLP using Python

Question

I have a sentence for which i need to identify the Person names alone:

For example:

sentence = "Larry Page is an American business magnate and computer scientist who is the co-founder of Google, alongside Sergey Brin"

I have used the below code to identify the NERs.

from nltk import word_tokenize, pos_tag, ne_chunk
print(ne_chunk(pos_tag(word_tokenize(sentence))))

The output i received was:

(S
  (PERSON Larry/NNP)
  (ORGANIZATION Page/NNP)
  is/VBZ
  an/DT
  (GPE American/JJ)
  business/NN
  magnate/NN
  and/CC
  computer/NN
  scientist/NN
  who/WP
  is/VBZ
  the/DT
  co-founder/NN
  of/IN
  (GPE Google/NNP)
  ,/,
  alongside/RB
  (PERSON Sergey/NNP Brin/NNP))

I want to extract all the person names, such as

Larry Page
Sergey Brin

In order to achieve this, I refereed this link and tried this.

from nltk.tag.stanford import StanfordNERTagger
st = StanfordNERTagger('/usr/share/stanford-ner/classifiers/english.all.3class.distsim.crf.ser.gz','/usr/share/stanford-ner/stanford-ner.jar')

However i continue to get this error:

LookupError: Could not find stanford-ner.jar jar file at /usr/share/stanford-ner/stanford-ner.jar

Where can i download this file?

As informed above, the result that i am expecting in the form of list or dictionary is :

Larry Page
Sergey Brin

Answer 1

In Long

Please read these carefully:

• https://stackoverflow.com/a/49345866/610569
• Extract list of Persons and Organizations using Stanford NER Tagger in NLTK

Understand the solution, don't just copy and paste.

---

TL;DR

In terminal:

pip install -U nltk

wget http://nlp.stanford.edu/software/stanford-corenlp-full-2016-10-31.zip
unzip stanford-corenlp-full-2016-10-31.zip && cd stanford-corenlp-full-2016-10-31

java -mx4g -cp "*" edu.stanford.nlp.pipeline.StanfordCoreNLPServer \
-preload tokenize,ssplit,pos,lemma,parse,depparse \
-status_port 9000 -port 9000 -timeout 15000

In Python

from nltk.tag.stanford import CoreNLPNERTagger

def get_continuous_chunks(tagged_sent):
    continuous_chunk = []
    current_chunk = []

    for token, tag in tagged_sent:
        if tag != "O":
            current_chunk.append((token, tag))
        else:
            if current_chunk: # if the current chunk is not empty
                continuous_chunk.append(current_chunk)
                current_chunk = []
    # Flush the final current_chunk into the continuous_chunk, if any.
    if current_chunk:
        continuous_chunk.append(current_chunk)
    return continuous_chunk


stner = CoreNLPNERTagger()
tagged_sent = stner.tag('Rami Eid is studying at Stony Brook University in NY'.split())

named_entities = get_continuous_chunks(tagged_sent)
named_entities_str_tag = [(" ".join([token for token, tag in ne]), ne[0][1]) for ne in named_entities]


print(named_entities_str_tag)

[out]:

[('Rami Eid', 'PERSON'), ('Stony Brook University', 'ORGANIZATION'), ('NY', 'LOCATION')]

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