Mate: Universal Tab Translator 6 1 4

Universal USB Installer aka UUI is a Live Linux Bootable USB Creator that allows you to choose from a selection of Linux Distributions to put on your USB Flash Drive. The Universal USB Installer is easy to use. Simply choose a Live Linux Distribution, the ISO file, your Flash Drive and, Click Install. Upon completion, you should have a ready to run bootable USB Flash Drive with your select operating system installed. Other features include; Persistence (if available) – Ubuntu, Xubuntu, and Lubuntu Casper Persistence feature works with FAT32 or NTFS formatted drives. Larger than 4GB casper-rw is possible only when the USB drive is formatted with the NTFS filesystem.

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Get the world's largest catalog of guitar, bass & ukulele chords, tabs, and lyrics to learn your favorite songs! Search for any song by type, difficulty, tuning, and rating. Focus on guitar techniques or discover songs for particular moments with collections from professional guitarists. Play 15,000+ popular songs in their original sound with Tonebridge Guitar Effects. Features:. Explore.

NOTE: If you are looking to add multiple Linux Distributions, System Diagnostic Tools, Antivirus Utilities, and Windows Installers to your bootable USB, use YUMI – Multiboot USB Software, instead.

Universal USB Installer (UUI) Screenshots

1. Italian luxury brand Gucci is selling a £1, 700 'Tartan cotton long smock shirt' for men to fight 'toxic masculinity stereotypes.' The garment is inspired by grunge looks from the '90s.
2. Translation procedures. He writes that, 'while translation methods relate to whole texts, translation procedures are used for sentences and the smaller units of language' (p.81). He goes on to refer to the following methods of translation:. Word-for-word translation: in which the SL word order is preserved.

Universal-USB-Installer-1.9.9.5.exe – October 14, 2020 – Changes
Removed Try via DD option. Moved Antergos and Mageia entries to use Grub to boot.

IMPORTANT: The Windows to Go option requires the USB be formatted NTFS with 20GB free disk space to hold the virtual disk. See FAQ for more info.

MD5: 3B38F7323FB48FB33A38E8E13E5A194D

IMPORTANT NOTE: Your USB drive must be Fat32/NTFS formatted, otherwise Syslinux will fail and your drive will NOT Boot.

Bootable USB Flash Drive Creation Requirements:

• Universal-USB-Installer-1.9.9.5.exe
• Windows Vista/7/8/10 or WINE to create the USB (Win 98/XP/2K WILL NOT Work!)
  
• *Fat32 or NTFS Formatted Flash Drive. MBR partition only GPT will not work!
• PC with a BIOS that can boot from USB
• Your Favorite Linux ISO

Feel free to inform me of unlisted Live Linux distributions or version revisions, and I will do my best to update Universal USB Installer (UUI) to support them.

Universal USB Installer Recent Changelog:

10/14/20 – Version 1.9.9.5: Removed Try via DD option. Moved Antergos and Mageia entries to use Grub for boot.
10/12/20 – Version 1.9.9.4: Updated to support Puppy Linux Fossapup64. Fixed Try Unlisted ISO (Grub) option. Updated to support newer CentOS installers. You must use an NTFS format on your USB when using the DVD ISO, because it is larger than 4GB.
08/04/20 – Version 1.9.9.3: Fixed broken links for Antergos, EasyPeasy, Xpud, and CubLinux.
07/28/20 – Version 1.9.9.2: Updated to support LinuxFX (aka: Windows FX or WinFX).
07/17/20 – Version 1.9.9.1: Support Ubuntu's 'writable' casper persistence file name.
12/04/19 – Version 1.9.9.0: Updated to support Clear Linux and Pop OS.
09/17/19 – Version 1.9.8.9: Updated to support Skywave Linux, and newer Knoppix. Corrected Ubuntu based persistent conditional statements.
06/01/19 – Version 1.9.8.8: Updated to support newer Archbang, ArchLinux, Manjaro, Dr.Web, and AntiX. Add support for KaOS, Pop OS, Bionic Pup, Emmabuntus, and MX Linux.
02/19/19 – Version 1.9.8.7: Updated to support initrd boot option for newer Ubuntu based distributions when USB drive is formatted NTFS. Added persistence option to Kodachi entry.

UUI can create a Bootable USB containing any of the following:

— Ubuntu 32/64 Bit —

• Ubuntu Desktop
• Xubuntu Desktop
• Kubuntu Desktop
• Lubuntu Desktop
• Edubuntu Desktop
• Ubuntu Studio
• *Ubuntu Server Installer
• **Ubuntu Alternate
• Mythbuntu Desktop
• Blackbuntu

— Linux Mint 32/64 Bit —

• Linux Mint

— Debian Live/Netinst 32/64 Bit —

• Debian Netinst
• *Debian Live

— Backtrack/Kali Versions —

• Kali Linux
• Backtrack

— Fedora 32/64 Bit —

• Fedora Desktop

— OpenSUSE 32/64 Bit —

• OpenSUSE 32bit
• *OpenSUSE 64bit

— Puppy Linux Based —

• Fatdog64
• Lighthouse Puppy
• Lucid Puppy
• Precise Puppy
• Puppy Arcade
• Puppy 4.3.1
• Racy Puppy
• Slacko Puppy
• Wary Puppy

— Linux Distros for Kids —

• DouDouLinux
• Qimo 4 Kids 2.0
• Sugar on a Stick

— Other Distros Alphabetical —

• AOMEI (Disk Cloning and Backup Tool)
• Acronis Rescue CD
• Android
• AntiX
• Antergos
• ArchBang
• ArchLinux
• ArtistX
• Aurora
• BackBox
• Baltix Linux
• BCCD
• BlehOS
• Bodhi
• Boot Repair Disk
• Carmedia
• CentOS
• Chakra
• Clonezilla
• Crunchbang
• DBAN 2.2.X
• Deft Linux
• Deepin Linux
• DRBL
• DSL 4.4.10
• Dreamlinux
• Dynebolic
• EASUS Disk Copy
• EasyPeasy
• Elementary OS
• Elementary Unleashed
• Feather Linux
• Finnix
• Fuduntu
• Fusion Linux
• Gamedrift
• Gentoo
• GEEXBOX
• gNewSense
• GRML
• gOS gadgets
• GParted
• Jolicloud
• Kiwi
• KNOPPIX
• Kororaa
• KXStudio
• Leeenux
• Liberte
• LinHES
• Linux XP Like
• LPS
• Macbuntu
• Mandriva One 2011
• Matriux
• MCNLive Toronto
• Meego
• MicroCore
• Netrunner
• Ophcrack
• OSGeo Live
• Pardus
• PartedMagic
• PCLinuxOS
• Pear OS
• Peppermint
• PING
• Pinguy OS
• Plasma active
• PLoP Linux
• Porteus
• Redo Backup
• Rescatux
• RIP Linux
• Runt Linux
• Sabayon Linux
• SalineOS
• Satux
• Simply MEPIS
• SLAX
• SliTaZ
• Sn0wL1nuX
• SolusOS
• System Rescue CD
• Tails
• Terralinux
• TinyCore
• Trisquel
• Uberstudent
• Ultimate Boot CD
• Ultimate Edition
• WifiWay
• WifiSlax
• xPUD
• XBMC
• XBMCbuntu
• StartOS
• wattOS R5
• Zenwalk Live
• Zorin OS

— Live Antivirus Rescue CDs —

• AOSS (Malware Scanner)
• AVG Rescue CD
• Avira Antivir Rescue Disk
• Bitdefender Rescue CD
• Comodo Rescue Disk
• DrWeb LiveCD
• F-Secure Rescue CD
• G DATA Antivirus
• Kaspersky Rescue Disk
• Panda Safe CD
• Trinity Rescue Kit

— Other Software —

• Falcon 4 Boot CD
• Hiren's Boot CD
• Kon-Boot

— Windows to Go + Windows Installers —

• Windows to Go (on VHD)
• *Windows Vista Installer
• **Windows 7 Installer
• ***Windows 8 Installer

— Try to use an Unsupported ISO —

• Try Unlisted Linux ISO

More Live Linux Distributions will be added as time permits. Feel free to contact me to submit recommendations.

UUI – Universal USB Installer Troubleshooting, Issues, Bugs:

The Windows to Go option requires the USB drive be NTFS formatted and have 20GB+ free space to hold the virtual disk. Many flash drives you might find at local department stores won't be fast enough. You'll need a Very Fast Flash Drive. When Windows boots from the USB for the first time, it'll go through the setup process and then reboot. You'll need to boot using your Windows to Go flash drive a second time to finalize the setup process and finally boot into your full Portable Windows.

UUI Expects the Volume Label of your USB drive to be UUI in order for OpenSUSE, CentOS and several other distributions to boot. UUI attempts to automatically create this Volume Label, however it can sometimes fail. Please ensure that the Volume Label of your USB remains UUI if you expect distributions to boot!

Persistence feature is currently broken with Newer Debian and Debian based distributions due to significant changes upstream. Debian now requires a rename of the persistent block file and label from live-rw to persistence and must hold a persistence.conf file containing / Union. I will be working on making the necessary changes to provide a fix as time allows.

If you're using Universal-USB-Installer-1.9.9.5.exe and you still receive Insane primary (MBR) partition notices,

Insane primary (MBR) partition. Can't find myself on the drive I booted from

Your USB drive may be improperly formatted, contains more than one partition or MBR, or your BIOS is not properly detecting the USB drive and its firmware needs to be updated. You can try these methods to Format and Restore your USB Drive

An Error (1) occurred while executing syslinux.

If you encounter a message stating

An error (1) occurred while executing syslinux. Your USB drive won't be bootable.

The most likely cause is that your USB drive is formatted as exFAT or some other unsupported format. You'll need to reformat as fat32 (currently preferred) or NTFS.

My PC wont Boot from my Flash Drive, but supports USB boot!

Many Flash Drives ship USB-FDD formatted and some systems will not detect or even boot USB-FDD. I have found that most systems can however boot USB-ZIP, and or USB-HDD. If you are having a hard time getting your BIOS to detect your flash drive, you can try to format it as USB-HDD or USB-ZIP using BOOTICE (GET IT HERE), and then proceed to use Universal USB Installer to put your chosen Distro on USB.

Android studio on macbook. OTHER IMPORTANT NOTES:

• If you're running a Windows Vista or 7 Installer from your USB, after the first reboot, remove the flash drive and let the pc complete from the hard disk.
• When browsing for an ISO, UUI will only display ISO Files that match exactly what the tool is asking for. For example, if you chose to install Ubuntu 10.10 Desktop i386, you should not expect the tool to display your ubuntu-10.10-netbook-i386.iso as you have not chosen to install the netbook variant.

Auto Detection: If you run Universal USB Installer from the same directory containing an installable ISO, the script should Auto Detect the ISO and bypass step 2.

* Although you can use an NTFS formatted USB, Ubuntu based 'persistence' features will only work with a Fat16 or Fat32 formatted drive. Additionally some Linux Distributions will not boot from an NTFS formatted USB.

This tool does not support adding, installing, and booting from multiple Linux Distributions. Only One Distribution can be installed per USB drive. However the YUMI Multiboot USB Creator can be used to create a Multi System USB Device.

To try an ISO that isn't listed, simply choose one of the the last three options in Step 1. I recommend 'Try Unlisted Linux ISO (GRUB)' because it seems to be the most successful. Please inform me of any unlisted 'Linux ISOs' you get to work via these options, and I'll make a note to add them to the list.

NOTE: OpenSUSE DVD ISOs that exceed 4GB will not work due to the Fat32 limitation.

Ubuntu Server 'Failed to copy file from CD-ROM' Error (should currently be resolved)?

The Universal USB Installer should run from within Linux using WINE. However, the Fat32 format option does not work. Additionally, Syslinux must be manually installed onto the USB when using UUI.

Universal USB Installer – Easy as 1 2 3 published under Bootable USB Creator Software

About | Citing |Questions |Download |Included Tools |Extensions |Release history |Sample output |Online |FAQ

Mate: Universal Tab Translator 6 1 4 0

About

A natural language parser is a program that works out the grammaticalstructure of sentences, for instance, which groups of words go together(as 'phrases') and which words are the subject or object of averb. Probabilistic parsers use knowledge of language gained fromhand-parsed sentences to try to produce the most likely analysis of newsentences. These statistical parsers still make some mistakes, butcommonly work rather well. Their development was one of the biggest breakthroughs innatural language processing in the 1990s. You can try out our parseronline.

Package contents

This package is a Java implementation of probabilistic natural languageparsers, both highly optimized PCFG and lexicalized dependency parsers, and alexicalized PCFG parser. The original version of this parser was mainly written by Dan Klein,with support code and linguistic grammar development by Christopher Manning. Extensive additional work (internationalization and language-specificmodeling, flexible input/output, grammar compaction, lattice parsing,k-best parsing,typed dependencies output,user support, etc.) has been done by Roger Levy, Christopher Manning,Teg Grenager, Galen Andrew, Marie-Catherine de Marneffe, BillMacCartney, Anna Rafferty, Spence Green, Huihsin Tseng, Pi-Chuan Chang, WolfgangMaier, and Jenny Finkel.

Calcbot 1 0 1 – intelligent calculator and unit converter. The lexicalized probabilistic parser implements a factored product model, with separate PCFG phrase structure and lexical dependency experts, whose preferences are combined by efficient exact inference, using an A* algorithm.Or the software can be used simply as an accurate unlexicalized stochasticcontext-free grammar parser.Either of these yields a good performance statistical parsing system.A GUI is provided for viewing the phrase structure tree output of the parser.

As well as providing an English parser, the parser can beand has been adapted to work with other languages.A Chinese parser based on the Chinese Treebank, a Germanparser based on the Negra corpus and Arabic parsers based on the Penn Arabic Treebank are also included.The parser has also been used for other languages, such as Italian,Bulgarian, and Portuguese.

The parser provides Universal Dependencies (v1) and Stanford Dependencies output as well as phrase structure trees. Typed dependencies areotherwise known grammatical relations. This style of output is available only for English and Chinese.For more details, please refer to the Stanford Dependencies webpage and the Universal Dependencies v1 documentation. (See also the current Universal Dependencies documentation, but we are yet to update to it.).

Shift-reduce constituency parser

As of version 3.4 in 2014, the parser includes the code necessary to run a shift reduce parser, a much faster constituent parser with competitive accuracy. Models for this parser are linked below.

Neural-network dependency parser

In version 3.5.0 (October 2014) we released a high-performance dependency parser powered by a neural network. The parser outputs typed dependency parses for English and Chinese. The models for this parser are included in the general Stanford Parser models package.

Dependency scoring

The package includes a tool for scoring of generic dependency parses, in a class edu.stanford.nlp.trees.DependencyScoring. This tool measures scores for dependency trees, doing F1 and labeled attachment scoring. The included usage message gives a detailed description of how to use the tool.

Usage notes

The current version of the parser requires Java 8 or later.(You can also download an old version of the parser, version 1.4,which runs under JDK 1.4, version 2.0 which runs under JDK 1.5, version 3.4.1which runs under JDK 1.6, but those distributions are no longer supported.)The parser also requires a reasonable amount of memory (at least 100MB to run as a PCFG parser on sentences up to 40 words in length; typically around 500MB of memory to be able to parse similarly long typical-of-newswire sentences using the factored model).

The parser is available for download,licensed under the GNUGeneral Public License (v2 or later). Source is included. The packageincludes components for command-line invocation, a Java parsingGUI, and a Java API.

The download is a 261 MB zipped file (mainly consisting of included grammar data files). If you unpack the zip file, you should have everything needed. Simple scripts are included to invoke the parser on a Unix or Windows system. For another system, you merely need to similarly configure the classpath.

Licensing

Mate: Universal Tab Translator 6 1 4 X 4

The parser code is dual licensed (in a similar manner to MySQL, etc.). Open source licensing is under the full GPL,which allows many free uses.For distributors of proprietarysoftware, commercial licensing is available.(Fine print: The traditional (dynamic programmed) Stanford Parser does part-of-speech tagging as it works, but the newer constituency and neural network dependency shift-reduce parsers require pre-tagged input. For convenience, we include the part-of-speech tagger code, but not models with the parser download. However, if you want to use these parsers under a commercial license, then you need a license to both the Stanford Parser and the Stanford POS tagger. Or you can get the whole bundle of Stanford CoreNLP.)If you don't need a commercial license, but would like to supportmaintenance of these tools, we welcome gift funding: use this form and write 'Stanford NLP Group open source software' in the Special Instructions.

The Universal USB Installer should run from within Linux using WINE. However, the Fat32 format option does not work. Additionally, Syslinux must be manually installed onto the USB when using UUI.

Universal USB Installer – Easy as 1 2 3 published under Bootable USB Creator Software

About | Citing |Questions |Download |Included Tools |Extensions |Release history |Sample output |Online |FAQ

Mate: Universal Tab Translator 6 1 4 0

About

A natural language parser is a program that works out the grammaticalstructure of sentences, for instance, which groups of words go together(as 'phrases') and which words are the subject or object of averb. Probabilistic parsers use knowledge of language gained fromhand-parsed sentences to try to produce the most likely analysis of newsentences. These statistical parsers still make some mistakes, butcommonly work rather well. Their development was one of the biggest breakthroughs innatural language processing in the 1990s. You can try out our parseronline.

Package contents

This package is a Java implementation of probabilistic natural languageparsers, both highly optimized PCFG and lexicalized dependency parsers, and alexicalized PCFG parser. The original version of this parser was mainly written by Dan Klein,with support code and linguistic grammar development by Christopher Manning. Extensive additional work (internationalization and language-specificmodeling, flexible input/output, grammar compaction, lattice parsing,k-best parsing,typed dependencies output,user support, etc.) has been done by Roger Levy, Christopher Manning,Teg Grenager, Galen Andrew, Marie-Catherine de Marneffe, BillMacCartney, Anna Rafferty, Spence Green, Huihsin Tseng, Pi-Chuan Chang, WolfgangMaier, and Jenny Finkel.

Calcbot 1 0 1 – intelligent calculator and unit converter. The lexicalized probabilistic parser implements a factored product model, with separate PCFG phrase structure and lexical dependency experts, whose preferences are combined by efficient exact inference, using an A* algorithm.Or the software can be used simply as an accurate unlexicalized stochasticcontext-free grammar parser.Either of these yields a good performance statistical parsing system.A GUI is provided for viewing the phrase structure tree output of the parser.

As well as providing an English parser, the parser can beand has been adapted to work with other languages.A Chinese parser based on the Chinese Treebank, a Germanparser based on the Negra corpus and Arabic parsers based on the Penn Arabic Treebank are also included.The parser has also been used for other languages, such as Italian,Bulgarian, and Portuguese.

The parser provides Universal Dependencies (v1) and Stanford Dependencies output as well as phrase structure trees. Typed dependencies areotherwise known grammatical relations. This style of output is available only for English and Chinese.For more details, please refer to the Stanford Dependencies webpage and the Universal Dependencies v1 documentation. (See also the current Universal Dependencies documentation, but we are yet to update to it.).

Shift-reduce constituency parser

As of version 3.4 in 2014, the parser includes the code necessary to run a shift reduce parser, a much faster constituent parser with competitive accuracy. Models for this parser are linked below.

Neural-network dependency parser

In version 3.5.0 (October 2014) we released a high-performance dependency parser powered by a neural network. The parser outputs typed dependency parses for English and Chinese. The models for this parser are included in the general Stanford Parser models package.

Dependency scoring

The package includes a tool for scoring of generic dependency parses, in a class edu.stanford.nlp.trees.DependencyScoring. This tool measures scores for dependency trees, doing F1 and labeled attachment scoring. The included usage message gives a detailed description of how to use the tool.

Usage notes

The current version of the parser requires Java 8 or later.(You can also download an old version of the parser, version 1.4,which runs under JDK 1.4, version 2.0 which runs under JDK 1.5, version 3.4.1which runs under JDK 1.6, but those distributions are no longer supported.)The parser also requires a reasonable amount of memory (at least 100MB to run as a PCFG parser on sentences up to 40 words in length; typically around 500MB of memory to be able to parse similarly long typical-of-newswire sentences using the factored model).

The parser is available for download,licensed under the GNUGeneral Public License (v2 or later). Source is included. The packageincludes components for command-line invocation, a Java parsingGUI, and a Java API.

The download is a 261 MB zipped file (mainly consisting of included grammar data files). If you unpack the zip file, you should have everything needed. Simple scripts are included to invoke the parser on a Unix or Windows system. For another system, you merely need to similarly configure the classpath.

Licensing

Mate: Universal Tab Translator 6 1 4 X 4

The parser code is dual licensed (in a similar manner to MySQL, etc.). Open source licensing is under the full GPL,which allows many free uses.For distributors of proprietarysoftware, commercial licensing is available.(Fine print: The traditional (dynamic programmed) Stanford Parser does part-of-speech tagging as it works, but the newer constituency and neural network dependency shift-reduce parsers require pre-tagged input. For convenience, we include the part-of-speech tagger code, but not models with the parser download. However, if you want to use these parsers under a commercial license, then you need a license to both the Stanford Parser and the Stanford POS tagger. Or you can get the whole bundle of Stanford CoreNLP.)If you don't need a commercial license, but would like to supportmaintenance of these tools, we welcome gift funding: use this form and write 'Stanford NLP Group open source software' in the Special Instructions.

Citing the Stanford Parser

The main technical ideas behind how these parsers work appear in thesepapers. Feel free to cite one or more of the following papers or people depending on what youare using. Since the parser is regularly updated, we appreciate it ifpapers with numerical results reflecting parser performance mention theversion of the parser being used!

For the neural-network dependency parser:
Danqi Chen and Christopher D Manning. 2014. A Fast and Accurate Dependency Parser using Neural Networks. Proceedings of EMNLP 2014

For the Compositional Vector Grammar parser (starting at version 3.2):
Richard Socher, John Bauer, Christopher D. Manning and Andrew Y. Ng. 2013.Parsing With Compositional Vector Grammars. Proceedings of ACL 2013

For the Shift-Reduce Constituency parser (starting at version 3.2):
This parser was written by John Bauer. You can thank him and cite the web page describing it: https://nlp.stanford.edu/software/srparser.html. You can also cite the original research papers of others mentioned on that page.

For the PCFG parser (which also does POS tagging):
Dan Klein and Christopher D. Manning. 2003. Accurate Unlexicalized Parsing. Proceedings of the 41st Meeting of the Association for Computational Linguistics, pp. 423-430.

For the factored parser (which also does POS tagging):
Dan Klein and Christopher D. Manning. 2003. Fast Exact Inference with a Factored Model for Natural Language Parsing. In Advancesin Neural Information Processing Systems 15 (NIPS 2002), Cambridge, MA: MIT Press, pp. 3-10.

For the Universal Dependencies representation:
Joakim Nivre, Marie-Catherine de Marneffe, Filip Ginter, Yoav Goldberg, Jan Hajič,Christopher D. Manning, Ryan McDonald, Slav Petrov, Sampo Pyysalo, Natalia Silveira,Reut Tsarfaty, and Daniel Zeman. 2016. Universal Dependencies v1: A Multilingual Treebank Collection. In LREC 2016.

For the English Universal Dependencies converter and the enhanced English Universal Dependencies representation:
Sebastian Schuster and Christopher D. Manning. 2016. Enhanced English Universal Dependencies: An Improved Representation for Natural Language Understanding Tasks.In LREC 2016.

For the (English) Stanford Dependencies representation:
Marie-Catherine de Marneffe, Bill MacCartney and Christopher D. Manning. 2006. GeneratingTyped Dependency Parses from Phrase Structure Parses. In LREC 2006.

For the German parser:
Anna Rafferty and Christopher D. Manning. 2008.Parsing Three German Treebanks: Lexicalized and Unlexicalized Baselines.In ACL Workshop on Parsing German.

For the Chinese Parser:
Roger Levy and Christopher D. Manning.2003.Is it harder to parse Chinese, or the Chinese Treebank?ACL 2003, pp. 439-446.

For the Chinese Stanford Dependencies:
Pi-Chuan Chang, Huihsin Tseng, Dan Jurafsky, and Christopher D. Manning.2009.Discriminative Reordering with Chinese Grammatical Relations Features.In Proceedings of the Third Workshop on Syntax and Structure in Statistical Translation.

For the Arabic parser:
Spence Green and Christopher D. Manning.2010.Better Arabic Parsing: Baselines, Evaluations, and Analysis.In COLING 2010.

For the French parser:
Spence Green, Marie-Catherine de Marneffe, John Bauer, and Christopher D. Manning.2010.Multiword Expression Identification with Tree Substitution Grammars: A Parsing tour de force with French.In EMNLP 2011.

For the Spanish parser:
Most of the work on Spanish was by Jon Gauthier. There is no published paper, but you can thank him and/or citethis webpage:https://nlp.stanford.edu/software/spanish-faq.html

Questions about the parser?

1. If you're new to parsing, you can start by running the GUI to tryout the parser. Scripts are included for linux (lexparser-gui.sh) andWindows (lexparser-gui.bat).
2. Take a look at the Javadoc lexparser packagedocumentation and LexicalizedParser class documentation.(Point your web browser at the index.html file in the included javadoc directory and navigate to those items.)
3. Look at the parser FAQ for answers to common questions.
4. If none of that helps, please see our emailguidelines for instructions on how to reach us for further assistance.

Download

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Extensions: Packages by others using the parser

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Java

• tydevi Typed DependencyViewer that makes a picture of the Stanford Dependencies analysis of a sentence. By Bernard Bou.
• DependenSee A Dependency Parse Visualisation Tool that makespictures of Stanford Dependency output. By Awais Athar. (GitHub)
• GATEplug-in. By the GATE Team (esp. Adam Funk).
• GrammarScopegrammatical relation browser. GUI, especially focusing on grammatical relations (typed dependencies), including an editor. ByBernard Bou.

PHP

• PHP-Stanford-NLP. Supports POS Tagger, NER, Parser. By Anthony Gentile (agentile).

Room arranger 9 0 – design your room office apartment. Python/Jython

• Pythoninterface built using JPype by Stefanie Tellex.
• Jython interface.by Viktor Pekar.

Ruby

• Ruby wrapper to theStanford Natural Language Parser. By Bill McNeill. An extended andbetter packaged version of this by John Wilkinson is available at github.

Dash 4 6 2. .NET / F# / C#

• Sergey Tihon has ported the Stanford Parser to F# (or any .NET language, including C#), using IKVM. See his blog post, his Github site, or the listing on NuGet.

OS X

• If you use Homebrew, you can install the Stanford Parser with:brew install stanford-parser

Release history

Sample input and output

The parser can read various forms of plain text input and can outputvarious analysis formats, including part-of-speech tagged text, phrasestructure trees, and a grammatical relations (typed dependency) format.For example, consider the text:

The strongest rain ever recorded in India shut down the financialhub of Mumbai, snapped communication lines, closed airports and forcedthousands of people to sleep in their offices or walk home during thenight, officials said today.

The following output showspart-of-speech tagged text, then a context-free phrase structure grammarrepresentation, and finally a typed dependency representation. All ofthese are different views of the output of the parser.

This output was generated with the command:

java -mx200m edu.stanford.nlp.parser.lexparser.LexicalizedParser-retainTMPSubcategories -outputFormat'wordsAndTags,penn,typedDependencies' englishPCFG.ser.gz mumbai.txt