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Install yamcha with Homebrew, MacPorts

NLP text chunker using Support Vector Machines. Version 0.33 via Homebrew; verified from local package data.

install

Additional install commands

macOS

Homebrewverified · 100%
brew install yamcha

local Homebrew formula metadata

MacPortsverified · 94%
sudo port install yamcha

MacPorts ports tree · textproc/yamcha/Portfile · source: api.github.com

overview

Package summary

NLP text chunker using Support Vector Machines

Commands and aliases

  • yamcha
  • yamcha-config
  • yamcha-mkmodel

history

Project history and usage

YamCha, Yet Another Multipurpose CHunk Annotator, is Taku Kudo's open-source text chunker built around support vector machines. It belongs to the pre-deep-learning generation of NLP packages where feature templates, chunk encodings, and SVM training pipelines were packaged as reusable command-line tools.

Project history

The official YamCha page describes it as a generic, customizable text chunker for POS tagging, named-entity recognition, base noun phrase chunking, and text chunking. It says the system used support vector machines and was the same system that performed best in the CoNLL-2000 shared task and a BaseNP chunking task.

The YamCha news log records an initial 0.1 release in July 2001, followed by a steady 2002-2005 sequence that added multi-class strategies, memory savings for large models, C API support, PKE acceleration, experimental Perl/Python/Ruby modules, 64-bit support, and bug fixes. The project page was last revised in late 2005, matching the period when SVM chunkers were a mainstream statistical NLP approach.

Adoption history

YamCha's adoption came through NLP research and language-processing pipelines rather than general developer tooling. The companion ACL paper, Chunking with Support Vector Machines, connects the software to the 2001 NAACL work by Kudo and Matsumoto and to the then-current practice of comparing chunkers on shared tasks.

The package remained relevant in Unix package managers because it bundled training and decoding commands plus a C/C++ library around TinySVM-era models. For users maintaining older NLP experiments, YamCha is a reproducibility and compatibility artifact as much as a current modeling choice.

How it is used

Typical use is to prepare token-per-line training or test data with feature columns and chunk labels, train a model with YamCha's template-driven SVM pipeline, and run the `yamcha` decoder or `yamcha-mkmodel` tooling. The official documentation emphasizes feature windows, parsing direction, pairwise versus one-vs-rest multiclass strategies, partial chunking, and model conversion for faster classification.

Why package nerds care

YamCha is historically significant because it packages a specific research-era NLP method into a reusable Unix tool. It sits beside ChaSen, TinySVM, CaboCha, CRF++, and MeCab in Taku Kudo's ecosystem of compact Japanese/NLP-oriented C and C++ tools that escaped academia into package managers.

Timeline

  • 2001: Kudo and Matsumoto published Chunking with Support Vector Machines at NAACL, and YamCha 0.1 was released in July.
  • 2002: YamCha 0.2 added multi-class strategy selection, memory savings for large model files, and broader compiler support.
  • 2004: YamCha 0.30 added PKE acceleration and a C API; 0.31 added experimental Perl, Python, and Ruby modules.
  • 2005: YamCha 0.33 added experimental 64-bit support and bag-of-words features.

Related projects

  • TinySVM is a direct dependency named by the official installation instructions.
  • ChaSen, CaboCha, CRF++, and MeCab are related Taku Kudo or Japanese NLP tools from the same broader ecosystem.

security posture

Risk level: green

narrow executable package without higher-risk signals.

Risk classifier

green risk · low confidence · appliance

Why

  • narrow executable package without higher-risk signals

Signals

  • metadata:no-higher-risk-signals

Install behavior

  • No Homebrew post-install hook is recorded in formula metadata.
  • Homebrew bottle metadata is available for 13 platform targets.
  • Installs with 1 runtime dependencies.
  • Build metadata lists 1 build dependencies.

Recommended review

Before unattended agent use, check whether the tool reads plaintext credentials, writes remote state, publishes artifacts, or shells out to plugins.

executables

Installed executables

CommandKindExposureNote
yamchacliglobal executable
yamcha-configcliglobal executable
yamcha-mkmodelcliglobal executable

freshness

Version and freshness

These signals separate page generation age, package-manager activity, and upstream release comparison. Version lag is warned only when an evidence URL and comparable versions are present.

page generated2026-07-08
manager version0.33
manager updated
local dataok
upstreamnot checked
latest detectednot detected

http://chasen.org/~taku/software/yamcha/

install metadata

Package metadata

Package keybrew:yamcha
Version0.33
Package managerHomebrew
Package manager pagehttps://formulae.brew.sh/formula/yamcha
Homepagehttp://chasen.org/~taku/software/yamcha/
Upstream docshttp://chasen.org/~taku/software/yamcha
LicenseLGPL-2.1-or-later
Source archivehttps://deb.debian.org/debian/pool/main/y/yamcha/yamcha_0.33.orig.tar.gz
Dependenciestinysvm
Build dependenciesautomake
Bottleavailable (on arm64_big_sur, arm64_linux, arm64_monterey, arm64_sequoia, arm64_sonoma, arm64_tahoe, arm64_ventura, big_sur, catalina, monterey, sonoma, ventura, x86_64_linux)
Homebrew post-installnot defined
Servicenone declared

registry facts

Source database details

Source DatabaseHomebrew formula API
Taphomebrew/core
Full Nameyamcha
Version Scheme0
Revision0
Bottle Stable Root URLhttps://ghcr.io/v2/homebrew/core
Deprecatedno
Disabledno
Keg Onlyno
URL Keys
  • stable

source database matches

Other package-manager records

Matches are pulled from external package-manager indexes and kept separate from local Automic Vault package links.

MacPorts95%

yamcha

sudo port install yamcha
  • normalized package name match
  • Matched by: Yamcha
MacPorts ports tree · api.github.com · MacPorts ports tree: textproc/yamcha/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1

source trail

Generated from repository data

This page is generated by av-web from the private package SQLite artifact built by scripts/generate-pkg-sqlite.py.

Used sources

  • Geiger risk classifier
  • Nucleus package database
  • av.db category and tag curation
  • cross-ecosystem install command graph
  • curated package history
  • external package-manager database matches
  • package relationship graph
  • package version freshness
  • package-page enrichment