HomeNamed Entity RecognitionText Analysis Online no longer provides NLTK Stanford NLP API Interface
Deep Learning Specialization on Coursera

Text Analysis Online no longer provides NLTK Stanford NLP API Interface, but keep the related demo just for testing:

NLTK Stanford POS Tagger: http://textanalysisonline.com/nltk-stanford-postagger

NLTK Stanford Named Entity Recognizer: http://textanalysisonline.com/nltk-stanford-ner

NLTK Stanford Named Entity Recognizer for 7Class: http://textanalysisonline.com/nltk-stanford-ner-7class

NLTK Stanford Named Entity Recognizer for Caseless: http://textanalysisonline.com/nltk-stanford-ner-caseless

NLTK Stanford Parser: http://textanalysisonline.com/nltk-stanford-parser

We recommend you use the original Stanford NLP Tools by Java: http://nlp.stanford.edu/software/

Which include:

Stanford CoreNLP
An integrated suite of natural language processing tools for English, Spanish, and (mainland) Chinese in Java, including tokenization, part-of-speech tagging, named entity recognition, parsing, and coreference. See also: Stanford Deterministic Coreference Resolution, the online CoreNLP demo, and the CoreNLP FAQ.
Stanford Parser
Implementations of probabilistic natural language parsers in Java: PCFG and dependency parsers, a lexicalized PCFG parser, a super-fast neural-network dependency parser, and a deep learning reranker. See also:Online parser demo, the Stanford Dependencies page, neural-network dependency parser documentation, and Parser FAQ.
Stanford POS Tagger
A maximum-entropy (CMM) part-of-speech (POS) tagger for English, Arabic, Chinese, French, German, and Spanish, in Java.
Stanford Named Entity Recognizer
A Conditional Random Field sequence model, together with well-engineered features for Named Entity Recognition in English, Chinese, German, and Spanish. Online NER demo.
Stanford Word Segmenter
A CRF-based word segmenter in Java. Supports Arabic and Chinese.
Stanford Classifier
A machine learning classifier, with good feature templates for text categorization. Provides a softmax (a.k.a., maximum entropy or multiclass logistic regression) classifier, Naive Bayes, and other options.
Tregex, Tsurgeon, and Semgrex
Tools for matching patterns in linguistic trees (following the tgrep/tgrep2 tradition), a GUI for this, and a tree-transformation utility built on top of this matching language. Also, a similar utility for matching patterns in dependency graphs.
Phrasal
A state-of-the-art phrase-based machine translation system.
Stanford EnglishTokenizer
A fast tokenizer for English text (producing Penn Treebank tokenization, roughly)
Stanford TokensRegex
A tool for matching regular expressions over tokens.
Stanford Temporal Tagger (SUTime)
A rule-based temporal tagger for English text. Online SUTime demo.
Stanford Pattern-based Information Extraction and Diagnostics (SPIED)
A boostrapped pattern-based entity extraction system.
Stanford Relation Extractor
A tool for extracting relations between entities.
GloVe: Global Vectors for Word Representations
Software in C for learning state-of-the-art distributed word representations, and a number of sets of pre-trained word vectors.
Topic Modeling Toolbox (TMT)
A suite of topic modeling tools for social scientists and others who wish to perform analysis on datasets that have a substantial textual component. Unfortunately, this software is no longer developed or supported.
Stanford Biomedical Event Parser (SBEP)
Biomedical Event Extraction for the BioNLP 2009/2011 shared task.

Posted by TextMiner

Deep Learning Specialization on Coursera

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