# stanford-ner を Homebrew, MacPorts でインストール

stanford-ner のインストール経路、実行ファイル、メタデータ、AI エージェント向けセキュリティノートを確認します。

## インストール

```sh
sudo av install brew:stanford-ner
```

追加のインストールコマンド:

### macOS

- Homebrew (100%):

```sh
brew install stanford-ner
```

  証拠: local Homebrew formula metadata

- MacPorts (94%):

```sh
sudo port install stanford-ner
```

  証拠: MacPorts ports tree: textproc/stanford-ner/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1

## パッケージ情報

- **パッケージキー:** brew:stanford-ner
- **パッケージマネージャ:** Homebrew
- **バージョン:** 4.2.0
- **ソース概要:** Stanford NLP Group's implementation of a Named Entity Recognizer
- **ホームページ:** <https://nlp.stanford.edu/software/CRF-NER.shtml>
- **最終更新:** 2026-06-22T14:06:23-07:00
- **生成日時:** 2026-08-03T19:37:03+00:00

## 実行可能ファイル

- ner-gui.sh (エイリアス)
- ner.sh (エイリアス)

## インストール挙動

- Bottle: 利用不可

## バージョンと鮮度

- ページ生成日: 2026-08-03
- マネージャ版: 4.2.0
## プロジェクトの歴史と使われ方

Stanford NER is the Stanford NLP Group's Java implementation of a named entity recognizer and CRF sequence-modeling tool. It is distributed both as a standalone Stanford NLP tool and as part of CoreNLP.

### プロジェクトの歴史

The official documentation describes Stanford NER as a Java implementation of named entity recognition and notes that it is also known as CRFClassifier. The page credits the original CRF code to Jenny Finkel, feature extractors to Dan Klein, Christopher Manning, and Jenny Finkel, and cites the 2005 ACL paper by Jenny Rose Finkel, Trond Grenager, and Christopher Manning.

### 採用の歴史

Stanford NER became package-manager relevant because it offered trained English models, a Java API, command-line scripts, and server usage from a single download. The official page lists wrappers or integrations for .NET, Perl, PHP, Python, Ruby, and UIMA, showing how the Java tool was embedded in other language ecosystems.

### 使われ方

Command-line usage loads Stanford NER jars and classifier models, then runs Java classes such as `edu.stanford.nlp.ie.NERClassifierCombiner` against text files. The package also includes a GUI, batch files or shell scripts, server support, and Java demo code.

### パッケージ好きにとっての重要性

Package maintainers care about Stanford NER because it packages a classic NLP model workflow: Java bytecode, large serialized classifiers, shell scripts, and model selection. A good package hides classpath friction and makes older research software usable from modern CLI workflows.

### タイムライン

- 2005: Finkel, Grenager, and Manning publish the cited ACL paper for the model and software.
- 2011: Stanford NLP documentation advises using matching releases of the Java NLP tools from 2011 onward.
- 2020: CoreNLP docs continue to document Stanford NER as an additional tool and CoreNLP annotator.

### Related projects

- Stanford NER is part of the broader Stanford JavaNLP/CoreNLP family and relates to CRFClassifier, Stanford POS Tagger, Stanford Parser, model jars, and language wrappers such as NLTK's Stanford NER interface.

### ソース

- <https://nlp.stanford.edu/software/CRF-NER.shtml: Stanford NLP software page with models and wrapper listings.>
- <https://stanfordnlp.github.io/CoreNLP/history.html: CoreNLP release context for Stanford JavaNLP tools.>
- <https://stanfordnlp.github.io/CoreNLP/tools_crf_ner.html: official NER overview, authorship, command-line/API/server notes, and citation.>


## セキュリティノート

narrow executable package without higher-risk signals.

- **Geiger リスク:** グリーン / 低
- narrow executable package without higher-risk signals

## 他のパッケージマネージャ記録

- MacPorts - stanford-ner: normalized package name match | MacPorts ports tree: textproc/stanford-ner/Portfile from https://api.github.com/repos/macports/macports-ports/git/trees/master?recursive=1


## Combined YAML source

View the package source record on GitHub. [combined/stanford-ner.yml](https://github.com/mxcl/pkgdb/blob/main/combined/stanford-ner.yml)


## ソース

- pkg.so package database
- Geiger risk classifier
- curated package history
- pkgdb category and tag curation
- external package-manager database matches
- cross-ecosystem install command graph