Help:Extension:翻譯/翻譯記憶

This page is a translated version of the page Help:Extension:Translate/Translation memories and the translation is 57% complete.
Outdated translations are marked like this.

翻译扩展的翻译记忆 支持ElasticSearch。该页面旨在指导您安装ElasticSearch,并更详细地探索其规格。

与其他翻译辅助工具(例如外部机器翻译服务)不同,翻译记忆库会不断更新您的维基中的新翻译。如果您选择使用ElasticSearch,也可以在Special:SearchTranslations中获得跨翻译的高级搜索。 Advanced search across translations is also available at Special:SearchTranslations if you choose to use ElasticSearch.

比较

The database backend is used by default: it has no dependencies and doesn't need configuration. The database backend can't be shared among multiple wikis and it does not scale to large amounts of translated content. Hence we also support ElasticSearch as a backend. It is also possible to use another wiki's translation memory if their web API is open. Unlike ElasticSearch, remote backends are not updated with translations from the current wiki.

数据库 远程 API ElasticSearch
默认为启用 No No
可含多个来源 No
随本地翻译更新 No
直接访问数据库 No No
访问来源 编者 链接 本地时编者,否则链接
可共享为 API 服务
表现 缩放不好 未知 合理的

条件

ElasticSearch 后端

ElasticSearch is relatively easy to set up. If it is not available in your distribution packages, you can get it from their website. You will also need to get the Elastica extension. Finally, please see puppet/modules/elasticsearch/files/elasticsearch.yml for specific configuration needed by Translate.

The bootstrap script will create necessary schemas. If you are using ElasticSearch backend with multiple wikis, they will share the translation memory by default, unless you set the index parameter in the configuration.

When upgrading to the next major version of ElasticSearch (e.g. upgrading from 2.x to 5.x), it is highly recommended to read the release notes and the documentation regarding the upgrade process.

安裝

在满足基本要求后,安装需要您调整配置,然后执行引导程序。

配置

包含翻译记忆的所有翻译辅助功能都通过$wgTranslateTranslationServices设置變數来配置。

The primary translation memory backend must use the key TTMServer. The primary backend receives translation updates and is used by Special:SearchTranslations.

TTMServers的配置示例:

默认配置
$wgTranslateTranslationServices['TTMServer'] = array(
        'database' => false, // Passed to wfGetDB
        'cutoff' => 0.75,
        'type' => 'ttmserver',
        'public' => false,
);
远程 API 配置
$wgTranslateTranslationServices['example'] = array(
        'url' => 'http://example.com/w/api.php',
        'displayname' => 'example.com',
        'cutoff' => 0.75,
        'timeout' => 3,
        'type' => 'ttmserver',
        'class' => 'RemoteTTMServer',
);
ElasticSearch后端配置
In this case the single back-end service will be used both for reads & writes.
$wgTranslateTranslationServices['TTMServer'] = array(
        'type' => 'ttmserver',
        'class' => 'ElasticSearchTTMServer',
        'cutoff' => 0.75,
        /*
         * See http://elastica.io/getting-started/installation.html
         * See https://github.com/ruflin/Elastica/blob/8.x/src/Client.php
        'config' => This will be passed to \Elastica\Client
         */
);
ElasticSearch多个后端配置(由MLEB 2017.04支持)
// 定义用于读取操作的默认服务
// 允许快速切换到另一个后端
// 'mirrors' configuration option is no longer supported since MLEB 2023.10
$wgTranslateTranslationDefaultService = 'cluster1';
$wgTranslateTranslationServices['cluster1'] = array(
        'type' => 'ttmserver',
        'class' => 'ElasticSearchTTMServer',
        'cutoff' => 0.75,
        /*
         * 定义要复制写入的服务列表。
         * 这里只允许“可写”服务。
         */
        'mirrors' => [ 'cluster2' ],
        'config' => [ 'servers' => [ 'host' => 'elastic1001.cluster1.mynet' ] ]
);
$wgTranslateTranslationServices['cluster2'] = array(
        'type' => 'ttmserver',
        'class' => 'ElasticSearchTTMServer',
        'cutoff' => 0.75,
        /*
         * 如果“cluster2”被定义为默认服务,它将开始将写入复制到“cluster1”。
         */
        'mirrors' => [ 'cluster1' ],
        'config' => [ 'servers' => [ 'host' => 'elastic2001.cluster2.mynet' ] ]
);
ElasticSearch multiple services with single readable service using writable configuration (supported by MLEB 2023.04)
With writable configuration the following rules are enforced:
  • If writable is specified, services marked as writable are considered write only and others are considered read only.
  • If no service is specified as writable then services are considered both readable and writable.
  • The default service must always be readable.

If a service is marked as writable, the mirrors configuration will not be allowed.

// Three services configured with one being readable and the others being writable.
$wgTranslateTranslationServices['dc0'] = [
	'type' => 'ttmserver',
	'class' => 'ElasticSearchTTMServer',
	'cutoff' => 0.75,
	// Default service cannot be marked as write-only
];

$wgTranslateTranslationServices['dc1'] = [
	'type' => 'ttmserver',
	'class' => 'ElasticSearchTTMServer',
	'cutoff' => 0.75,
	// Marks this service as write-only 
	'writable' => true,
];

$wgTranslateTranslationServices['dc2'] = [
	'type' => 'ttmserver',
	'class' => 'ElasticSearchTTMServer',
	'cutoff' => 0.75,
	'writable' => true
];

$wgTranslateTranslationDefaultService = 'dc0';

可能的键值为:

用于 说明
config ElasticSearch 傳遞給Elastica的配置。
cutoff 所有 匹配建议的最小阀值。尽管在阀值上有更多合法值,但仅显示一些最佳建议。
database 本地 如果您想保存翻译记忆到不同位置,则可以在此处指定数据库名。同时还必须配置 MediaWiki 的负载均衡器以确定连接到该数据库的方法。
displayname 远程 悬停在建议来源链接(子弹头图标)时,工具提示中显示的文本。
index ElasticSearch 在ElasticSearch中使用的索引。默认值:ttmserver。
public 所有 该 TTMServer 是否可通过本 wiki 的 api.php 查询。
replicas ElasticSearch 如果您正在运行群集,则可以增加副本数。默认值:0。
shards ElasticSearch 要使用多少个分片。默认值:5。
timeout 远程 等待远程服务应答的秒數。
type 所有 以最终格式表示的 TTMServer 类型。
url 远程 远程 TTMServer 中 api.php 的链接。
use_wikimedia_extra ElasticSearch Boolean, when the extra plugin is deployed you can disable dynamic scripting on Elastic v1.x. This plugin is now mandatory for Elastic 2.x clusters.
mirrors (DEPRECATED Since MLEB 2023.04) Writable services 字符串数组定义了要复制写入的服务列表,它允许多个TTM服务保持最新。对于快速切换或减少计划维护操作期间的停机时间非常有用(在MLEB 2017.04中添加) Cannot be used along with the newly added writable configuration.
writable (Added in MLEB 2023.04) Write-only services Boolean value, defined for a service if that service is write-only. The default service (wgTranslateTranslationDefaultService) cannot be marked as write-only. If out of all the translation memory services configured, none are marked as writable then all services are considered to be readable and writable. 参见任务 T322284
要让翻译记忆与新译文一起更新,您必须使用TTMServer做為到$wgTranslateTranslationServices的陣列索引。远程TTMServer无法实现此功能,因为它们无法更新。 As of MLEB 2017.04 the key TTMServer can be configured with the configuration variable $wgTranslateTranslationDefaultService. Support for Solr backend was dropped in MLEB-2019.10, in October, 2019.

目前只支持MySQL数据库後端。

Bootstrap

Once you have chosen ElasticSearch and set up the requirements and configuration, run ttmserver-export.php to bootstrap the translation memory. Bootstrapping is also required when changing translation memory backend. If you are using a shared translation memory backend for multiple wikis, you'll need to bootstrap each of them separately.

Sites with lots of translations should consider using multiple threads with the --thread parameter to speed up the process. The time depends heavily on how complete the message group completion stats are (incomplete ones will be calculated during the bootstrap). New translations are automatically added by a hook. New sources (message definitions) are added when the first translation is created.

Bootstrap does the following things, which don't happen otherwise:

  • adding and updating the translation memory schema;
  • populating the translation memory with existing translations;
  • cleaning up unused translation entries by emptying and re-populating the translation memory.

When the translation of a message is updated, the previous translation is removed from the translation memory. However, when translations are updated against a new definition, a new entry is added but the old definition and its old translations remain in the database until purged. When a message changes definition or is removed from all message groups, nothing happens immediately. Saving a translation as fuzzy does not add a new translation nor delete an old one in the translation memory.

TTMServer API

如果您想实现自己的 TTMServer 数据库,请看详细说明。

查询参数:

您的服务必须接受下列参数:

format json
action ttmserver
service 存在多个共享翻译记忆时可选的服务标识符。如果未提供,则使用默认服务。
sourcelanguage 如同 MediaWiki 中使用的语言代码,请参阅 IETF 语言标记和 ISO693?
targetlanguage 如同 MediaWiki 中使用的语言代码,请参阅 IETF 语言标记和 ISO693?
test 源语言表示的原内容

您的服务必须提供对象数组中含有键 ttmserver 的 JSON 对象。这些对象必须包含下列数据: Those objects must contain the following data:

source 原始的源文本。
target 翻译建议。
context 源的本地标识符,可选。
location 到查看建议的网页链接。
quality 表示建议且在 [0..1] 区间的十进制数。1 表示最佳匹配。

例如:

{
        "ttmserver": [
                {
                        "source": "January",
                        "target": "tammikuu",
                        "context": "Wikimedia:Messages\\x5b'January'\\x5d\/en",
                        "location": "https:\/\/translatewiki.net\/wiki\/Wikimedia:Messages%5Cx5b%27January%27%5Cx5d\/fi",
                        "quality": 0.85714285714286
                },
                {
                        "source": "January",
                        "target": "tammikuu",
                        "context": "Mantis:S month january\/en",
                        "location": "https:\/\/translatewiki.net\/wiki\/Mantis:S_month_january\/fi",
                        "quality": 0.85714285714286
                },
                {
                        "source": "January",
                        "target": "Tammikuu",
                        "context": "FUDforum:Month 1\/en",
                        "location": "https:\/\/translatewiki.net\/wiki\/FUDforum:Month_1\/fi",
                        "quality": 0.85714285714286
                },
                {
                        "source": "January",
                        "target": "tammikuun",
                        "context": "MediaWiki:January-gen\/en",
                        "location": "https:\/\/translatewiki.net\/wiki\/MediaWiki:January-gen\/fi",
                        "quality": 0.85714285714286
                },
                {
                        "source": "January",
                        "target": "tammikuu",
                        "context": "MediaWiki:January\/en",
                        "location": "https:\/\/translatewiki.net\/wiki\/MediaWiki:January\/fi",
                        "quality": 0.85714285714286
                }
        ]
}

数据库后端

后端包含了三个表:translate_tmstranslate_tmttranslate_tmf。分别对应于源、目标和完整的文本。您可以在 sql/translate_tm.sql 中看到表格的定义。源包含了所有信息组定义。尽管通常它们总是使用相同的语言(例如英语),但在极少数情况下,文本的语言也会存储,这是不正确的。 Those correspond to sources, targets and fulltext. You can find the table definitions in sql/translate_tm.sql. The sources contain all the message definitions. Even though usually they are always in the same language, say, English, the language of the text is also stored for the rare cases this is not true.

每个条目都有唯一的 ID 和两个附加字段:长度和上下文。查询时使用长度作为首个过滤器,这样就无需把要搜索的文本和数据库中每个条目进行比较。上下文中保存了文本来源的页面标题,例如“MediaWiki:Jan/en”。根据该信息,我们可以把建议链接到“MediaWiki:Jan/de”,这样有助于译者快速修复问题或确定使用哪个译文。 Length is used as the first pass filter, so that when querying we don't need to compare the text we're searching with every entry in the database. The context stores the title of the page where the text comes from, for example MediaWiki:Jan/en. From this information we can link the suggestions back to MediaWiki:Jan/de, which makes it possible for translators to quickly fix things, or just to determine where that kind of translation was used.

第二个过滤器来自全文索引。它的定义与 ad hoc 算法混合。首先通过 MediaWiki 的 Language::segmentByWord 把文本分割为片段(词)。如果有足够的片段,我们主要去除所有非单词字母的那些内容来常态化。接着获取开头的十个唯一单词,必须至少五个字节长(英文中的五个字母,对于多字节字符则更少字数)。然后把这些词保存在全文索引中供将来过滤更长的字符串。 The definitions are mingled with an ad hoc algorithm. First the text is segmented into segments (words) with MediaWiki's Language::segmentByWord. If there are enough segments, we strip basically everything that is not word letters and normalize the case. Then we take the first ten unique words, which are at least 5 bytes long (5 letters in English, but even shorter words for languages with multibyte code points). Those words are then stored in the fulltext index for further filtering for longer strings.

过滤出候选列表后,则从目标表中获取匹配的目标。然后使用编辑距离算法进行最后的过滤和排序。定义如下:

E
编辑距离
S
用于搜索建议的文本
Tc
建议文本
To
译文 Tc 的原始文本

通过 E/min(length(Tc),length(To)) 计算 Tc 建议的质量。我们使用 PHP 内置的 levenshtein 函数,但当某个字符串长于 255 字节时,则使用 PHP 实现的 levenshtein 算法。[1] It has not been tested whether the native implementation of levenshtein handles multibyte characters correctly. This might be another weak point when source language is not English (the others being the fulltext search and segmentation).