Query responses and response types

Amazon Kendra supports different query responses and response types.

Query responses

A call to the Query API returns information about the results of a search. The results are in an array ofQueryResultItem objects (ResultItems). Each QueryResultItem includes a summary of the result. Document attributes associated with the query result are included.

Summary information

The summary information varies depending on the type of result. In each case, it includes document text that matches the search term. It also includes highlight information that you can use to highlight the search text in your application's output. For example, if the search term is what is the height of the Space Needle?, the summary information includes text location for the words height and space needle. For information about response types, see Query responses and response types.

Document attributes

Each result contains document attributes for the document that matches a query. Some of the attributes are predefined, such as DocumentId, DocumentTitle, and DocumentUri. Others are custom attributes that you define. You can use document attributes to filter the response from the Query API. For example, you might want only the documents written by a specific author or a specific version of a document. For more information, see Filtering and facet search. You specify document attributes when you add documents to an index. For more information, see Custom fields or attributes.

The following is sample JSON code for a query result. Note the document attributes in DocumentAttributes and AdditionalAttributes.

{
    "QueryId": "query-id",
    "ResultItems": [
        {
            "Id": "result-id",
            "Type": "ANSWER",
            "AdditionalAttributes": [
                {
                    "Key": "AnswerText",
                    "ValueType": "TEXT_WITH_HIGHLIGHTS_VALUE",
                    "Value": {
                        "TextWithHighlightsValue": {
                            "Text": "text",
                            "Highlights": [
                                {
                                    "BeginOffset": 55,
                                    "EndOffset": 90,
                                    "TopAnswer": false
                                }
                            ]
                        }
                    }
                }
            ],
            "DocumentId": "document-id",
            "DocumentTitle": {
                "Text": "title"
            },
            "DocumentExcerpt": {
                "Text": "text",
                "Highlights": [
                    {
                        "BeginOffset": 0,
                        "EndOffset": 300,
                        "TopAnswer": false
                    }
                ]
            },
            "DocumentURI": "uri",
            "DocumentAttributes": [],
            "ScoreAttributes": "score",
            "FeedbackToken": "token"
        },
        {
            "Id": "result-id",
            "Type": "ANSWER",
            "Format": "TABLE",
            "DocumentId": "document-id",
            "DocumentTitle": {
                "Text": "title"
            },
            "TableExcerpt": {
                "Rows": [{
                    "Cells": [{
                        "Header": true,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    }, {
                        "Header": true,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    }, {
                        "Header": true,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    }, {
                        "Header": true,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    }]
                }, {
                    "Cells": [{
                        "Header": false,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    }, {
                        "Header": false,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    }, {
                        "Header": false,
                        "Highlighted": true,
                        "TopAnswer": true,
                        "Value": "value"
                    }, {
                        "Header": false,
                        "Highlighted": false,
                        "TopAnswer": false,
                        "Value": "value"
                    ]}
                  }],
                    "TotalNumberofRows": number
			},
            "DocumentURI": "uri",
            "ScoreAttributes": "score",
            "FeedbackToken": "token"
        },
        {
            "Id": "result-id",
            "Type": "DOCUMENT",
            "AdditionalAttributes": [],
            "DocumentId": "document-id",
            "DocumentTitle": {
                "Text": "title",
                "Highlights": []
            },
            "DocumentExcerpt": {
                "Text": "text",
                "Highlights": [
                    {
                        "BeginOffset": 74,
                        "EndOffset": 77,
                        "TopAnswer": false
                    }
                ]
            },
            "DocumentURI": "uri",
            "DocumentAttributes": [
                {
                    "Key": "_source_uri",
                    "Value": {
                        "StringValue": "uri"
                    }
                }
            ],
            "ScoreAttributes": "score",
            "FeedbackToken": "token",
        }
    ],
    "FacetResults": [],
    "TotalNumberOfResults": number
}

Response types

Amazon Kendra returns three types of query response.

• Answer (includes table answer)

• Document

• Question and answer

The type of the response is returned in the Type response field of the QueryResultItem object.

Answer

Amazon Kendra detected one or more question answers in the response. A factoid is the response to a who, what, when, or where question such as Where is the nearest service center to me? Amazon Kendra returns text in the index that best matches the query. The text is in the AnswerText field and contains highlight information for the search term within the response text. AnswerText includes the full document excerpt with highlighted text, while DocumentExcerpt includes the truncated (290 characters) document excerpt with highlighted text.

Amazon Kendra only returns one answer per document, and that is the answer with the highest confidence. To return multiple answers from a document, you must split the document into multiple documents.

{
    'AnswerText': {
        'TextWithHighlights': [
            {
                'BeginOffset': 271,
                'EndOffset': 279,
                'TopAnswer': False
            },
            {
                'BeginOffset': 481,
                'EndOffset': 489,
                'TopAnswer': False
            },
            {
                'BeginOffset': 547,
                'EndOffset': 555,
                'TopAnswer': False
            },
            {
                'BeginOffset': 764,
                'EndOffset': 772,
                'TopAnswer': False
            }
        ],
        'Text': 'Asynchronousoperationscan\n''alsoprocess\n''documentsthatareinPDF''format.UsingPDFformatfilesallowsyoutoprocess''multi-page\n''documents.\n''Forinformationabouthow''AmazonTextractrepresents\n''documentsasBlockobjects,
        ''seeDocumentsandBlockObjects.\n''\n''\n''\n''Forinformationaboutdocument''limits,
        seeLimitsinAmazonTextract.\n''\n''\n''\n''TheAmazonTextractsynchronous''operationscanprocessdocumentsstoredinanAmazon\n''S3Bucketoryoucanpass''base64encodedimagebytes.\n''Formoreinformation,
        see''CallingAmazonTextractSynchronousOperations.''Asynchronousoperationsrequireinputdocuments\n''tobesuppliedinanAmazon''S3Bucket.'
    },
    'DocumentExcerpt': {
        'Highlights': [
            {
                'BeginOffset': 0,
                'EndOffset': 300,
                'TopAnswer': False
            }
        ],
        'Text': 'Asynchronousoperationscan\n''alsoprocess\n''documentsthatareinPDF''format.UsingPDFformatfilesallowsyoutoprocess''multi-page\n''documents.\n''ForinformationabouthowAmazon''Textractrepresents\n'''
    },
    'Type': 'ANSWER'
}

Document

Amazon Kendra returns ranked documents for those that match the search term. The ranking is based on the confidence that Amazon Kendra has in the accuracy of the search result. Information about the matching document is returned in the QueryResultItem. It includes the title of the document. The excerpt includes highlight information for search text and the section of matching text in the document. The URI for matching documents is in the SourceURI document attribute. The following sample JSON shows the document summary for a matching document.

{
    'DocumentTitle': {
        'Highlights': [
            {
                'BeginOffset': 7,
                'EndOffset': 15,
                'TopAnswer': False
            },
            {
                'BeginOffset': 97,
                'EndOffset': 105,
                'TopAnswer': False
            }
        ],
        'Text': 'AmazonTextractAPIPermissions: Actions,
        \n''Permissions,
        andResourcesReference-''AmazonTextract'
    },
    'DocumentExcerpt': {
        'Highlights': [
            {
                'BeginOffset': 68,
                'EndOffset': 76,
                'TopAnswer': False
            },
            {
                'BeginOffset': 121,
                'EndOffset': 129,
                'TopAnswer': False
            }
        ],
        'Text': '...LoggingandMonitoring\tMonitoring\n''\tCloudWatchMetricsforAmazonTextract\n''\tLoggingAmazonTextractAPICallswithAWSCloudTrail\n''\tAPIReference\tActions\tAnalyzeDocument\n''\tDetectDocumentText\n''\tGetDocumentAnalysis...'
    },
    'Type': 'DOCUMENT'
}

Question and answer

A question and answer response is returned when Amazon Kendra matches a question with one of the frequently asked questions in your index. The response includes the matching question and answer in the QueryResultItem field. It also includes highlight information for query terms detected in query string. The following JSON shows a question and answer response. Note that the response includes the question text.

{
    'AnswerText': {
        'TextWithHighlights': [
            
        ],
        'Text': '605feet'
    },
    'DocumentExcerpt': {
        'Highlights': [
            {
                'BeginOffset': 0,
                'EndOffset': 8,
                'TopAnswer': False
            }
        ],
        'Text': '605feet'
    },
    'Type': 'QUESTION_ANSWER',
    'QuestionText': {
        'Highlights': [
            {
                'BeginOffset': 12,
                'EndOffset': 18,
                'TopAnswer': False
            },
            {
                'BeginOffset': 26,
                'EndOffset': 31,
                'TopAnswer': False
            },
            {
                'BeginOffset': 32,
                'EndOffset': 38,
                'TopAnswer': False
            }
        ],
        'Text': 'whatistheheightoftheSpaceNeedle?'
    }
}

For information about adding question and answer text to an index, see Creating FAQ.