CogComp-NLP provides a suite of state-of-the-art Natural Language Processing (NLP) tools that allows you to annotate plain text inputs.
There’s a JVM API and a Python API.
CogComp NLP Pipeline bundles some basic preprocessing steps that a lot of NLP applications need, with the goal of making them run locally.
CogComp Corpusreaders includes NLP Corpus readers that reads into datastructures provided by the cogcomp-core-utilities package.
CogComp’s main NLP libraries provide the following modules – test an NLP annotator.
- nlp-pipeline – provides an end-to-end NLP processing application that runs a variety of NLP tools on input text.
- core-utilities – provides a set of NLP-friendly data structures and a number of NLP-related utilities that support writing NLP applications, running experiments, etc.
- corpusreaders – provides classes to read documents from corpora into core-utilities data structures.
- curator – supports use of CogComp NLP Curator, a tool to run NLP applications as services.
- edison – a library for feature extraction from core-utilities data structures. Edison is a feature extraction framework that uses the data structures of core-utilities to extract features used in NLP applications. The library is using a Feature Extraction Language (FEX) as a declarative way of defining features.
- lemmatizer – an application that uses WordNet and simple rules to find the root forms of words in plain text.
- tokenizer – an application that identifies sentence and word boundaries in plain text.
- transliteration – an application that transliterates names between different scripts.
- pos – an application that identifies the part of speech (e.g. verb + tense, noun + number) of each word in plain text.
- ner – an application that identifies named entities in plain text according to two different sets of categories.
- md – an application that identifies entity mentions in plain text.
- relation-extraction – an application that identifies entity mentions, then identify relation pairs among the mentions detected.
- quantifier – this tool detects mentions of quantities in the text, as well as normalizes it to a standard form.
- inference – a suite of unified wrappers to a set optimization libraries, as well as some basic approximate solvers.
- depparse – an application that identifies the dependency parse tree of a sentence.
- verbsense – this system addresses the verb sense disambiguation (VSD) problem for English.
- prepsrl – an application that identifies semantic relations expressed by prepositions and develops statistical learning models for predicting the relations.
- commasrl – this software extracts relations that commas participate in.
- similarity – this software compare objects –especially Strings– and return a score indicating how similar they are.
- temporal-normalizer – a temporal extractor and normalizer.
- dataless-classifier – classifies text into a user-specified label hierarchy from just the textual label descriptions
- external-annotators – a collection useful external annotators.
Website: cogcomp.seas.upenn.edu
Support: GitHub Code Repository
Developer: Cognitive Computation Group
License: Research and Academic Use License
CogComp-NLP is written in Java. Learn Java with our recommended free books and free tutorials.
Related Software
| Java Natural Language Processing Tools | |
|---|---|
| CoreNLP | Annotation-based NLP pipeline that provides core natural language analysis |
| OpenNLP | Machine learning based toolkit |
| DL4J | Deploy and train deep learning models |
| Lucene | High-performance, full-featured information retrieval software library |
| UIMA | Open source implementation of the UIMA specification |
| Tika | Content analysis toolkit |
| MALLET | Statistical natural language processing, document classification and more |
| GATE | Full-lifecycle solution for a broad range of NLP tasks |
| ReVerb | Automatically identifies and extracts binary relationships from sentences |
| NLP4J | NLP framework for JVM languages |
| CogComp-NLP | State-of-the-art Natural Language Processing (NLP) tools |
Read our verdict in the software roundup.
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