同义词图分词过滤器
synonym_graph 分词过滤器是 synonym 分词过滤器的一个更高级版本。它支持多词同义词，并处理多个分词之间的同义词，使其非常适合短语或分词间关系重要的场景。
参数
synonym_graph 分词过滤器可以通过以下参数进行配置。
| 参数 | 必需/可选 | 数据类型 | 描述 |
|---|---|---|---|
synonyms | 必须指定 synonyms 或 synonyms_path | 字符串 | 直接在配置中定义的同义词规则列表。 |
synonyms_path | 必须指定 synonyms 或 synonyms_path | 字符串 | 包含同义词规则的文件的文件路径（可以是绝对路径，也可以是相对于配置目录的路径）。 |
lenient | 可选 | 布尔型 | 加载规则配置时是否忽略异常。默认为 false。 |
format | 可选 | 字符串 | 指定用于确定 OpenSearch 如何定义和解释同义词的格式。有效值为 - solr- wordnet。默认为 solr。 |
expand | 可选 | 布尔型 | 是否扩展等效同义词规则。默认为 true。例如 如果 synonyms 定义为 "quick, fast" 且 expand 设置为 true，则同义词规则配置如下：- quick => quick- quick => fast- fast => quick- fast => fast如果 expand 设置为 false，则同义词规则配置如下：- quick => quick- fast => quick |
示例：Solr 格式
以下示例请求创建了一个名为 my-index 的新索引，并配置了一个带有 synonym_graph 过滤器的分析器。该过滤器配置为默认的 solr 规则格式。
PUT /my-index
{
"settings": {
"analysis": {
"filter": {
"my_synonym_graph_filter": {
"type": "synonym_graph",
"synonyms": [
"sports car, race car",
"fast car, speedy vehicle",
"luxury car, premium vehicle",
"electric car, EV"
]
}
},
"analyzer": {
"my_synonym_graph_analyzer": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"my_synonym_graph_filter"
]
}
}
}
}
}
生成的词元
使用以下请求检查使用该分析器生成的词元
GET /my-car-index/_analyze
{
"analyzer": "my_synonym_graph_analyzer",
"text": "I just bought a sports car and it is a fast car."
}
响应包含生成的词元
{
"tokens": [
{"token": "i","start_offset": 0,"end_offset": 1,"type": "<ALPHANUM>","position": 0},
{"token": "just","start_offset": 2,"end_offset": 6,"type": "<ALPHANUM>","position": 1},
{"token": "bought","start_offset": 7,"end_offset": 13,"type": "<ALPHANUM>","position": 2},
{"token": "a","start_offset": 14,"end_offset": 15,"type": "<ALPHANUM>","position": 3},
{"token": "race","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 4},
{"token": "sports","start_offset": 16,"end_offset": 22,"type": "<ALPHANUM>","position": 4,"positionLength": 2},
{"token": "car","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 5,"positionLength": 2},
{"token": "car","start_offset": 23,"end_offset": 26,"type": "<ALPHANUM>","position": 6},
{"token": "and","start_offset": 27,"end_offset": 30,"type": "<ALPHANUM>","position": 7},
{"token": "it","start_offset": 31,"end_offset": 33,"type": "<ALPHANUM>","position": 8},
{"token": "is","start_offset": 34,"end_offset": 36,"type": "<ALPHANUM>","position": 9},
{"token": "a","start_offset": 37,"end_offset": 38,"type": "<ALPHANUM>","position": 10},
{"token": "speedy","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 11},
{"token": "fast","start_offset": 39,"end_offset": 43,"type": "<ALPHANUM>","position": 11,"positionLength": 2},
{"token": "vehicle","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 12,"positionLength": 2},
{"token": "car","start_offset": 44,"end_offset": 47,"type": "<ALPHANUM>","position": 13}
]
}
示例：WordNet 格式
以下示例请求创建了一个名为 my-wordnet-index 的新索引，并配置了一个带有 synonym_graph 过滤器的分析器。该过滤器配置为 wordnet 规则格式。
PUT /my-wordnet-index
{
"settings": {
"analysis": {
"filter": {
"my_synonym_graph_filter": {
"type": "synonym_graph",
"format": "wordnet",
"synonyms": [
"s(100000001, 1, 'sports car', n, 1, 0).",
"s(100000001, 2, 'race car', n, 1, 0).",
"s(100000001, 3, 'fast car', n, 1, 0).",
"s(100000001, 4, 'speedy vehicle', n, 1, 0)."
]
}
},
"analyzer": {
"my_synonym_graph_analyzer": {
"type": "custom",
"tokenizer": "standard",
"filter": [
"lowercase",
"my_synonym_graph_filter"
]
}
}
}
}
}
生成的词元
使用以下请求检查使用该分析器生成的词元
GET /my-wordnet-index/_analyze
{
"analyzer": "my_synonym_graph_analyzer",
"text": "I just bought a sports car and it is a fast car."
}
响应包含生成的词元
{
"tokens": [
{"token": "i","start_offset": 0,"end_offset": 1,"type": "<ALPHANUM>","position": 0},
{"token": "just","start_offset": 2,"end_offset": 6,"type": "<ALPHANUM>","position": 1},
{"token": "bought","start_offset": 7,"end_offset": 13,"type": "<ALPHANUM>","position": 2},
{"token": "a","start_offset": 14,"end_offset": 15,"type": "<ALPHANUM>","position": 3},
{"token": "race","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 4},
{"token": "fast","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 4,"positionLength": 2},
{"token": "speedy","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 4,"positionLength": 3},
{"token": "sports","start_offset": 16,"end_offset": 22,"type": "<ALPHANUM>","position": 4,"positionLength": 4},
{"token": "car","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 5,"positionLength": 4},
{"token": "car","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 6,"positionLength": 3},
{"token": "vehicle","start_offset": 16,"end_offset": 26,"type": "SYNONYM","position": 7,"positionLength": 2},
{"token": "car","start_offset": 23,"end_offset": 26,"type": "<ALPHANUM>","position": 8},
{"token": "and","start_offset": 27,"end_offset": 30,"type": "<ALPHANUM>","position": 9},
{"token": "it","start_offset": 31,"end_offset": 33,"type": "<ALPHANUM>","position": 10},
{"token": "is","start_offset": 34,"end_offset": 36,"type": "<ALPHANUM>","position": 11},
{"token": "a","start_offset": 37,"end_offset": 38,"type": "<ALPHANUM>","position": 12},
{"token": "sports","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 13},
{"token": "race","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 13,"positionLength": 2},
{"token": "speedy","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 13,"positionLength": 3},
{"token": "fast","start_offset": 39,"end_offset": 43,"type": "<ALPHANUM>","position": 13,"positionLength": 4},
{"token": "car","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 14,"positionLength": 4},
{"token": "car","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 15,"positionLength": 3},
{"token": "vehicle","start_offset": 39,"end_offset": 47,"type": "SYNONYM","position": 16,"positionLength": 2},
{"token": "car","start_offset": 44,"end_offset": 47,"type": "<ALPHANUM>","position": 17}
]
}