沃森NLU从不返回消歧信息

Question

我试图使用Watson会话和Watson NLU的组合来提取实体，并将它们与列表进行比较。我需要访问返回的消歧信息，但它不会返回我输入的任何内容。

它是正确提取公司，地点，人员等作为实体，和正确的分类。但是没有一个实体有消歧信息。我遗漏了什么吗？所有实体都有dbpedia条目(我手动检查过)。

例如：

"entities": [
    {
      "type": "Organization",
      "text": "NHS",
      "sentiment": {
        "score": 0,
        "label": "neutral"
      },
      "relevance": 0.949001,
      "count": 1
    },
    {
      "type": "Company",
      "text": "IBM",
      "sentiment": {
        "score": 0.497916,
        "label": "positive"
      },
      "relevance": 0.643598,
      "count": 1
    }
  ],

更新：

我尝试输入CNN，就像API文档中的示例一样，这是可行的：

"entities": [
    {
      "type": "Company",
      "text": "CNN",
      "sentiment": {
        "score": 0,
        "label": "neutral"
      },
      "relevance": 0.33,
      "disambiguation": {
        "subtype": [
          "Broadcast",
          "AwardWinner",
          "RadioNetwork",
          "TVNetwork"
        ],
        "name": "CNN",
        "dbpedia_resource": "http://dbpedia.org/resource/CNN"
      },
      "count": 1
    }
  ],

但其他什么都不是。它只对一小部分实体起作用吗？

Answer 1

我尝试在请求中发送以下正文

{
    "text":"IBM is a company based in Newyork",
    "features": {
    "entities":{}}
}

它返回带有消歧信息的输出。

{
"usage": {
    "text_units": 1,
    "text_characters": 33,
    "features": 1
},
"language": "en",
"entities": [
{
    "type": "Company",
    "text": "IBM",
    "relevance": 0.33,
    "disambiguation": {
        "subtype": [
            "SoftwareLicense",
            "OperatingSystemDeveloper",
            "ProcessorManufacturer",
            "SoftwareDeveloper",
            "CompanyFounder",
            "ProgrammingLanguageDesigner",
            "ProgrammingLanguageDeveloper"
        ],
        "name": "IBM",
        "dbpedia_resource": "http://dbpedia.org/resource/IBM"
    },
    "count": 2
},
{
    "type": "Location",
    "text": "Newyork",
    "relevance": 0.33,
    "disambiguation": {
        "subtype": [
            "City"
        ]
    },
    "count": 1
}
]
}

尽管如此，它确实返回了DBpedia URI中的大多数条目--您仍然无法获得与DBpedia URI有关的大信息，将您发送的请求文本作为评论发布。