macOS
Homebrewverified · 100%
brew install yamchalocal Homebrew formula metadata
MacPortsverified · 94%
sudo port install yamchaMacPorts ports tree · textproc/yamcha/Portfile · source: api.github.com
brew / rank 11922
Install yamcha with Homebrew, MacPorts
NLP text chunker using Support Vector Machines. Version 0.33 via Homebrew; verified 2026-07-11. Also installable with macports: sudo port install yamcha.
install
Additional install commands
overview
Package summary
NLP text chunker using Support Vector Machines
Project links
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.
Sources
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 bottle metadata was recorded.
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
| Command | Kind | Exposure | Note |
|---|---|---|---|
yamcha | executable | indexed executable | Discovered from the local executable index. |
yamcha-config | executable | indexed executable | Discovered from the local executable index. |
yamcha-mkmodel | executable | indexed executable | Discovered from the local executable index. |
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 generated2026-08-03
manager version0.33
manager updated2026-07-11
local dataunknown
upstreamnot available
latest detectednot detected
- okNo freshness warnings were generated.
install metadata
Package metadata
| Package key | brew:yamcha |
|---|---|
| Version | 0.33 |
| Package manager | Homebrew |
| Homepage | http://chasen.org/~taku/software/yamcha/ |
| Last updated | 2026-07-11T12:24:37-04:00 |
| Pulse | updated |
| Bottle | not recorded |
| Service | none declared |
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
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.
Combined YAML source
View the package source record on GitHub.
Used sources
- Geiger risk classifier
- cross-ecosystem install command graph
- curated package history
- external package-manager database matches
- pkg.so package database
- pkgdb category and tag curation