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
-1
votes
1 answer

Is it possible to subclass a spacy entity type?

I'd like to subclass the existing GPE, so that it differentiates between GPE-Nation, USA, and GPE-City, New York. I see in the docs how to create new entity types, but not how to subclass what's already there. Can this be done, and if so, how?…
Malik A. Rumi
  • 1,855
  • 4
  • 25
  • 36
-1
votes
2 answers

Shoud i use Spacy Named Entity Recognition for this case?

I have a set of names, a fixed set of names which can extend up-to 50,000 names. "John","Mike","Josh","Peter","Karl". And I have a document, this document is dynamic. I need to find whether this document has the predefined name or not ? Is defining…
user3383301
  • 1,891
  • 3
  • 21
  • 49
-1
votes
1 answer

stanfordNER training does not recognize GPU present in the environment

I have GPU(Tesla K80) present in the environment with CUDA installed. I am training stanfordNER on large data set with this Java command java -Xms8g -cp stanford-corenlp-3.9.1.jar edu.stanford.nlp.ie.crf.CRFClassifier -prop self.trainPropFileName. …
Sai krishna Telukuntla
  • 1
  • 1
-1
votes
1 answer

How do I extract values from a string and use those values in a database query?

I'm trying to extract custom entities from a sentence/question and query them against a database, the problem is that I'm having trouble with the extraction of entities. My table has 10,000s of rows and looks like this: Car type |…
crossemup
  • 351
  • 1
  • 3
  • 9
-1
votes
1 answer

NER for predefined entities

I'm developing a application to categorize requirements in a requirement specification in to categories like database, front end, back end, etc. Requirement specification is a single document where I want to see the underlying categories in it. Can…
rayan carlon
  • 9
  • 2
-1
votes
2 answers

NameError: name 'ne_chunk' is not defined

I am currently learning named-entity recognition using NLTK. Here is my code: from nltk.chunk import conlltags2tree, tree2conlltags from pprint import pprint iob_tagged = tree2conlltags(cs) pprint(iob_tagged) ne_tree =…
venikputri
  • 13
  • 1
  • 5
-1
votes
1 answer

Separate list of Common_noun proper noun and location in python

I have a list of words and I need to find out which words fall in the categories proper noun, common noun and location. I would like to have a table where each category has its proper column. My input is as…
Cyley Simon
  • 253
  • 2
  • 5
  • 17
-1
votes
2 answers

Stanford NLP NER, Sentiment, SUTime Performance Issue

The text in the main method seem to be taking more than 2 seconds to return NER. I am not an expert in NLP and this code is not at all scalable. I have added comments in 2 places where the bottleneck i have identified. Can you please suggest…
akay
  • 27
  • 9
-1
votes
1 answer

Identifying specific parts of a document using CRF

My goal is given a set of documents (mostly in financial domain), we need to identify specific parts of it like Company Name or Type of the document, etc. The training is assumed to be done on acouple of 100's of documents. Obviously I would have a…
sir_osthara
  • 154
  • 2
  • 9
-1
votes
3 answers

Tagging and Training NER dataset

I have a data set and I want to tag it for Named Entity Recognition. My dataset is in Persian. I want to know how should I tag expressions like : *** آقای مهدی کاظمی = Mr Mehdi Kazemi / Mr will Smith. >>> (names with titles) should I tag all as a…
Hedieh
  • 43
  • 8
-1
votes
1 answer

Does Stanford NER detect duplicate Entity mentions?

Let’s take an example of a text: “Barack Obama is an American politician serving as the 44th President of the United States. Born in Honolulu, Hawaii, Obama is a graduate of Columbia University and Harvard Law School.” Below screenshot is how the 4…
Akash Chawla
  • 1
  • 1
-1
votes
2 answers

NLP : What are some common verbs surrounding organization names in text

I am trying to come up with some rules to detect named entities, specifically company or organization names in text. I think it makes sense to focus on verbs. There are a lot of POS Taggers that can easily detect proper nouns. I personally like…
AbtPst
  • 7,778
  • 17
  • 91
  • 172
-1
votes
1 answer

Is there a combined model which can generate both POS and NER tags using Stanford's NLP Library

Here is an example of a sample text output: Good/NNP afternoon/NNP Rajat/PERSON Raina/PERSON,/O how/WRB are/VBP you/PRP today/NN ?/O
user3396081
  • 1
-1
votes
1 answer

How to use Wikipedia API to expand entities?

I'm working on my thesis and I encountered a problem i don't know hot to approach properly. I'm clustering tweets and given the few information they carry, I want to expand the entities I find in the text by accesing Wikipedia and taking the…
alex_vkcr
  • 64
  • 5
-1
votes
2 answers

Name Extraction - CV/Resume - Stanford NER/OpenNLP

I'm currently on a learning project to extract an individuals name from their CV/Resume. Currently I'm working with Stanford-NER and OpenNLP which both perform with a degree of success out of the box on, tending to struggle on "non-western" type…
Chris
  • 129
  • 1
  • 14
1 2 3
…
96
97