Match a Resume🔗︎
| HTTP Verb | Path |
|---|---|
| POST | /v10/matcher/resume |
Match a parsed resume to resumes/jobs in certain indexes.
Info
- You can try this endpoint out at our Swagger page ( US Data Center | EU Data Center | AU Data Center )
Request Body🔗︎
ResumeData 🔗︎ object required
ResumeData🔗︎
Parsed ResumeData from the Textkernel CV/Resume Parser. See Parse a Resume
IndexIdsToSearchInto 🔗︎ string[] required
IndexIdsToSearchInto🔗︎
The ids of the indexes in which you want to find results (case-insensitive).
PreferredCategoryWeights 🔗︎ object
PreferredCategoryWeights🔗︎
The weights you want to use for scoring. It is important to specify these, otherwise default values will be used.
These weights will be used except in the case that you provided a non-zero weight for a category that is irrelevant in the source document. For example, this can happen when the source document contains no languages.
PreferredCategoryWeights properties
JobTitles 🔗︎ decimal
JobTitles🔗︎
The weight of the JobTitles category relative to other categories..
Industries 🔗︎ decimal
Industries🔗︎
The weight of the Industries/Taxonomies category relative to other categories.
Certifications 🔗︎ decimal
Certifications🔗︎
The weight of the Certifications category relative to other categories.
Settings 🔗︎ object
Settings🔗︎
Options to control variations of job titles.
Settings properties
PositionTitlesMustHaveAnExactMatch 🔗︎ bool
PositionTitlesMustHaveAnExactMatch🔗︎
Set to true to turn off variation matches in job titles.
NormalizeJobTitles 🔗︎ bool
NormalizeJobTitles🔗︎
Normalize the first three job titles specified in FilterCriteria.JobTitles and automatically include them in the query. Additional charges apply.
You will only benefit from using this parameter if the data in your index was parsed with Professions Normalization enabled.
Normalized job titles help identify more matches by looking beyond the exact job title. Normalization uses lists of synonyms behind the scenes. For example, a search for "HR Advisor" will also return results for "Human Resources Consultant".
When matching, the normalized job title is automatically included in the query if the data in your index was parsed with Professions Normalization enabled.
NormalizeJobTitlesLanguage 🔗︎ string
NormalizeJobTitlesLanguage🔗︎
Specify the language (ISO 639-1 code) of the Job Title to be normalized. This defaults to en. See list of supported languages.
FilterCriteria 🔗︎ object
FilterCriteria🔗︎
Additional criteria for the result set.
FilterCriteria properties
RevisionDateRange 🔗︎ object
RevisionDateRange🔗︎
When specified, the revision date of documents must fall within this range.
RevisionDateRange properties
DocumentIds 🔗︎ string[]
DocumentIds🔗︎
Results must have one of the specified document ids (case-insensitive).
UserDefinedTags 🔗︎ string[]
UserDefinedTags🔗︎
List of user-defined tags. Either all or at least one are required depending on the value of FilterCriteria.UserDefinedTagsMustAllExist.
UserDefinedTagsMustAllExist 🔗︎ bool
UserDefinedTagsMustAllExist🔗︎
When true, all of the user-defined tags in FilterCriteria.UserDefinedTags must be found. By default, this is false, which means that at least one of the FilterCriteria.UserDefinedTags must be found.
LocationCriteria 🔗︎ object[]
LocationCriteria🔗︎
Filter results based on location.
LocationCriteria properties
Locations 🔗︎ object[]
Locations🔗︎
Results must be found within a certain distance of one of the specified locations.
Locations properties
DistanceUnit 🔗︎ string
DistanceUnit🔗︎
The units for the specified distance. One of:
- Miles
- Kilometers
SearchExpression 🔗︎ string
SearchExpression🔗︎
Full-text boolean semantic expresion. For full details on the syntax and supported operations refer to the documentation
HasSecurityCredentials 🔗︎ bool
HasSecurityCredentials🔗︎
If true, results must have/require security credentials. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators.
SecurityCredentials 🔗︎ string[]
SecurityCredentials🔗︎
Results must have/require at least one of the security credentials specified.
IsPublicSpeaker 🔗︎ bool
IsPublicSpeaker🔗︎
If true, results must have/require public speaking experience.
SchoolNames 🔗︎ string[]
SchoolNames🔗︎
Results must have at least one of the specified school names. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators
DegreeNames 🔗︎ string[]
DegreeNames🔗︎
Results must have at least one of the specified degree names. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators.
DegreeTypes 🔗︎ string[]
DegreeTypes🔗︎
Results must have at least one of the specified degree types. One of the following explicit values as defined by HROpenStandards.org, in increasing order:
- specialeducation
- someHighSchoolOrEquivalent
- ged
- secondary
- highSchoolOrEquivalent
- certification
- vocational
- someCollege
- HND_HNC_OrEquivalent
- associates
- international
- bachelors
- somePostgraduate
- masters
- intermediategraduate
- professional
- postprofessional
- doctorate
- postdoctorate
Employers 🔗︎ string[]
Employers🔗︎
Results must have at least one of the employers in FilterCriteria.Employers. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators.
EmployersMustAllBeCurrentEmployer 🔗︎ bool
EmployersMustAllBeCurrentEmployer🔗︎
When true, at least one employer in FilterCriteria.Employers must be found in the current time frame.
MonthsExperience 🔗︎ object
MonthsExperience🔗︎
When specified, results total work experieince must fall within this range.
MonthsExperience properties
DocumentLanguages 🔗︎ string[]
DocumentLanguages🔗︎
Results must be written in one of the specified languages.
Skills 🔗︎ object[]
Skills🔗︎
Results must have/require at least one of the specified skills.
Skills properties
SkillName 🔗︎ string
SkillName🔗︎
The name of the skill. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators.
SkillsMustAllExist 🔗︎ bool
SkillsMustAllExist🔗︎
When true, all of the skills in FilterCriteria.Skills must be found. By default, this is false, which means that at least one of the FilterCriteria.Skills must be found.
IsTopStudent 🔗︎ bool
IsTopStudent🔗︎
Results must have an education with a normalized gpa of .75 or higher (for example, 3.0/4.0 or higher).
JobTitles 🔗︎ object[]
JobTitles🔗︎
Results must have at least one of the specified job titles.
JobTitles properties
Title 🔗︎ string
Title🔗︎
The name of the Job Title. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators.
ExecutiveType 🔗︎ string[]
ExecutiveType🔗︎
Results must have at least one of the following types of executive:
- None
- Executive
- Admin
- Accounting
- Operations
- Financial
- Marketing
- Business_Dev
- IT
- General
- Learning
Certifications 🔗︎ string[]
Certifications🔗︎
Results must have at least one of the specified certifications. Supports (*, ?) wildcard characters after the third character in the term as defined in Special Operators.
MonthsManagementExperience 🔗︎ object
MonthsManagementExperience🔗︎
Results must have the management experience specified in this months range.
MonthsManagementExperience properties
CurrentManagementLevel 🔗︎ string
CurrentManagementLevel🔗︎
Results must currently have at least one of the following management levels:
- None
- Low
- Mid
- High
LanguagesKnown 🔗︎ string[]
LanguagesKnown🔗︎
List of ISO 639-1 codes (lower case, two letters) representing languages known. Either all or at least one are required depending on the value of FilterCriteria.LanguagesKnownMustAllExist.
LanguagesKnownMustAllExist 🔗︎ bool
LanguagesKnownMustAllExist🔗︎
When true, all of the languages in FilterCriteria.LanguagesKnown must be found. By default, this is false, which means that at least one of the FilterCriteria.LanguagesKnown must be found.
Taxonomies 🔗︎ string[]
Taxonomies🔗︎
Results must contain at least one of the specified best-fit taxonomy IDs or best-fit subtaxonomy IDs. A list of our built-in taxonomy IDs can be found here.
AverageMonthsPerEmployer 🔗︎ object
AverageMonthsPerEmployer🔗︎
Results must have an average months per employers specified in this range. Only applicable for resumes; setting this when filtering jobs will cause an error.
AverageMonthsPerEmployer properties
Sample JSON
{
"ResumeData": "...",
"IndexIdsToSearchInto": [
""
],
"Take": 0,
"PreferredCategoryWeights": {
"Education": 0,
"JobTitles": 0,
"Skills": 0,
"Industries": 0,
"Languages": 0,
"Certifications": 0,
"ExecutiveType": 0,
"ManagementLevel": 0
},
"Settings": {
"PositionTitlesMustHaveAnExactMatch": false,
"NormalizeJobTitles": false,
"NormalizeJobTitlesLanguage": ""
},
"FilterCriteria": {
"RevisionDateRange": {
"Minimum": "",
"Maximum": ""
},
"DocumentIds": [
""
],
"UserDefinedTags": [
""
],
"UserDefinedTagsMustAllExist": false,
"LocationCriteria": {
"Locations": [
{
"CountryCode": "",
"Region": "",
"Municipality": "",
"PostalCode": "",
"GeoPoint": {
"Latitude": 0,
"Longitude": 0
}
}
],
"Distance": 0,
"DistanceUnit": "Miles",
"GeocodeProvider": "None",
"GeocodeProviderKey": ""
},
"SearchExpression": "",
"HasPatents": false,
"HasSecurityCredentials": false,
"SecurityCredentials": [
""
],
"IsAuthor": false,
"IsPublicSpeaker": false,
"IsMilitary": false,
"SchoolNames": [
""
],
"DegreeNames": [
""
],
"DegreeTypes": [
""
],
"Employers": [
""
],
"EmployersMustAllBeCurrentEmployer": false,
"MonthsExperience": {
"Minimum": 0,
"Maximum": 0
},
"DocumentLanguages": [
""
],
"Skills": [
{
"SkillName": "",
"ExperienceLevel": "",
"IsCurrent": false
}
],
"SkillsMustAllExist": false,
"IsTopStudent": false,
"IsCurrentStudent": false,
"IsRecentGraduate": false,
"JobTitles": [
{
"Title": "",
"IsCurrent": false
}
],
"ExecutiveType": [
""
],
"Certifications": [
""
],
"MonthsManagementExperience": {
"Minimum": 0,
"Maximum": 0
},
"CurrentManagementLevel": "",
"LanguagesKnown": [
""
],
"LanguagesKnownMustAllExist": false,
"Taxonomies": [
""
],
"AverageMonthsPerEmployer": {
"Minimum": 0,
"Maximum": 0
},
"JobPredictiveIndex": {
"Minimum": 0,
"Maximum": 0
}
}
}
Response Body🔗︎
Info 🔗︎ object
Info🔗︎
Information explaining the outcome of the transaction.
Info properties
Code 🔗︎ string
Code🔗︎
| Code | Description |
|---|---|
Success |
Successful transaction |
MissingParameter |
A required parameter wasn't provided |
ConstraintError |
A conditionally required parameter wasn't provided |
InvalidParameter |
A parameter was incorrectly specified |
AuthenticationError |
An error occurred with the credentials provided |
Unauthorized |
Your account doesn't have permission to perform this operation |
DataNotFound |
Couldn't find the requested asset |
TransactionId 🔗︎ string
TransactionId🔗︎
The (GUID) id for a specific API transaction. Use this when contacting support@textkernel.com about issues.
EngineVersion 🔗︎ string
EngineVersion🔗︎
The version of the parsing/matching engine running under-the-hood.
TotalElapsedMilliseconds 🔗︎ integer
TotalElapsedMilliseconds🔗︎
How long the transaction took on Textkernel's server, in milliseconds. If the transaction takes longer to complete on the client side, that extra duration is solely network latency.
CustomerDetails 🔗︎ object
CustomerDetails🔗︎
Information about the customer who made the API call.
CustomerDetails properties
CreditsRemaining 🔗︎ decimal
CreditsRemaining🔗︎
The number of credits remaining to be used by the account.
Value 🔗︎ object
Value🔗︎
Contains response data for the transaction.
Value properties
Matches 🔗︎ object[]
Matches🔗︎
An object[] containing the results for each match result.
Matches properties
SovScore 🔗︎ integer
SovScore🔗︎
An integer score representing the overall fit of the match. Results are sorted by this parameter in descending order.
EnrichedScoreData 🔗︎ object
EnrichedScoreData🔗︎
Detailed information about the source to target match.
EnrichedScoreData properties
Languages 🔗︎ object
Languages🔗︎
Detailed match information for the Languages category.
Languages properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Certifications 🔗︎ object
Certifications🔗︎
Detailed match information for the Certifications category.
Certifications properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
ExecutiveType 🔗︎ object
ExecutiveType🔗︎
Detailed match information for the ExecutiveType category.
ExecutiveType properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Education 🔗︎ object
Education🔗︎
Detailed match information for the Eduction category.
Education properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Taxonomies 🔗︎ object
Taxonomies🔗︎
Detailed match information for the Taxonomies category.
Taxonomies properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ActualTaxonomies 🔗︎ object
ActualTaxonomies🔗︎
Taxonomies found.
ActualTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
DesiredTaxonomies 🔗︎ object
DesiredTaxonomies🔗︎
Taxonomies requested.
DesiredTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
JobTitles 🔗︎ object
JobTitles🔗︎
Detailed match information for the JobTitles category.
JobTitles properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
Skills 🔗︎ object
Skills🔗︎
Detailed match information for the Skills category.
Skills properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ManagementLevel 🔗︎ object
ManagementLevel🔗︎
Detailed match information for the ManagementLevel category.
ManagementLevel properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
EnrichedRCSScoreData 🔗︎ object
EnrichedRCSScoreData🔗︎
Detailed information about the target to source match.
EnrichedRCSScoreData properties
Languages 🔗︎ object
Languages🔗︎
Detailed match information for the Languages category.
Languages properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Certifications 🔗︎ object
Certifications🔗︎
Detailed match information for the Certifications category.
Certifications properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
ExecutiveType 🔗︎ object
ExecutiveType🔗︎
Detailed match information for the ExecutiveType category.
ExecutiveType properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Education 🔗︎ object
Education🔗︎
Detailed match information for the Eduction category.
Education properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Taxonomies 🔗︎ object
Taxonomies🔗︎
Detailed match information for the Taxonomies category.
Taxonomies properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ActualTaxonomies 🔗︎ object
ActualTaxonomies🔗︎
Taxonomies found.
ActualTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
DesiredTaxonomies 🔗︎ object
DesiredTaxonomies🔗︎
Taxonomies requested.
DesiredTaxonomies properties
Primary 🔗︎ object
Primary🔗︎
Best fit taxonomy evidence.
Primary properties
JobTitles 🔗︎ object
JobTitles🔗︎
Detailed match information for the JobTitles category.
JobTitles properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
Skills 🔗︎ object
Skills🔗︎
Detailed match information for the Skills category.
Skills properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
Evidence 🔗︎ object[]
Evidence🔗︎
Detailed written explanation about each data point found or not found.
Evidence properties
ManagementLevel 🔗︎ object
ManagementLevel🔗︎
Detailed match information for the ManagementLevel category.
ManagementLevel properties
UnweightedScore 🔗︎ double
UnweightedScore🔗︎
An unweighted score from 0-100. This is the percentage match of the specified category.
WeightedScore 🔗︎ integer
WeightedScore🔗︎
An integer score from 0-100 representing how well the source document matched the current document. This calculation is the sum of the unweighted category scores multiplied by their respective suggested weight.
ReverseCompatibilityScore 🔗︎ integer
ReverseCompatibilityScore🔗︎
An integer score from 0-100 which represents how well the target document matched to the source document. This isn't the same as WeightedScore because when doing the reverse calculation we are analyzing for all of the data from the target document to be found in the source document.
SuggestedCategoryWeights 🔗︎ object
SuggestedCategoryWeights🔗︎
The weights suggested by Textkernel based solely on the data in the source document.
NOTE: these should only be used as a fallback or initial value. Your system/users should have the ability to adjust/override these (in the PreferredCategoryWeights in the request)
SuggestedCategoryWeights properties
JobTitles 🔗︎ decimal
JobTitles🔗︎
The weight of the JobTitles category relative to other categories..
Industries 🔗︎ decimal
Industries🔗︎
The weight of the Industries/Taxonomies category relative to other categories.
Certifications 🔗︎ decimal
Certifications🔗︎
The weight of the Certifications category relative to other categories.
ExecutiveType 🔗︎ decimal
ExecutiveType🔗︎
The weight of the ExecutiveType category relative to other categories.
ManagementLevel 🔗︎ decimal
ManagementLevel🔗︎
The weight of the ManagementLevel category relative to other categories..
EducationHasData 🔗︎ boolean
EducationHasData🔗︎
If false, the Education category has no data and should be ignored/hidden.
JobTitlesHasData 🔗︎ boolean
JobTitlesHasData🔗︎
If false, the JobTitles category has no data and should be ignored/hidden.
SkillsHasData 🔗︎ boolean
SkillsHasData🔗︎
If false, the Skills category has no data and should be ignored/hidden.
IndustriesHasData 🔗︎ boolean
IndustriesHasData🔗︎
If false, the Industries/Taxonomies category has no data and should be ignored/hidden.
LanguagesHasData 🔗︎ boolean
LanguagesHasData🔗︎
If false, the Languages category has no data and should be ignored/hidden.
CertificationsHasData 🔗︎ boolean
CertificationsHasData🔗︎
If false, the Certifications category has no data and should be ignored/hidden.
AppliedCategoryWeights 🔗︎ object
AppliedCategoryWeights🔗︎
The weights that were actually used for scoring. These are either
1) if the PreferredCategoryWeights are specified in the request, these are used (with any adjustments for non-applicable categories)
2) otherwise these are simply the SuggestedCategoryWeights
AppliedCategoryWeights properties
JobTitles 🔗︎ decimal
JobTitles🔗︎
The weight of the JobTitles category relative to other categories..
Industries 🔗︎ decimal
Industries🔗︎
The weight of the Industries/Taxonomies category relative to other categories.
Certifications 🔗︎ decimal
Certifications🔗︎
The weight of the Certifications category relative to other categories.
CurrentCount 🔗︎ integer
CurrentCount🔗︎
The number of results that were returned. This number will never be greater than the Take in the request.
Sample JSON
{
"Info": {
"Code": "string",
"Message": "string",
"TransactionId": "string",
"EngineVersion": "string",
"ApiVersion": "string",
"TotalElapsedMilliseconds": 0,
"TransactionCost": 0,
"CustomerDetails": {
"AccountId": "string",
"Name": "string",
"IPAddress": "string",
"Region": "string",
"CreditsRemaining": 0,
"CreditsUsed": 0,
"ExpirationDate": "2021-12-31",
"MaximumConcurrentRequests": 0
}
},
"Value": {
"Matches": [
{
"Id": "",
"IndexId": "",
"SovScore": 0,
"EnrichedScoreData": {
"Languages": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Certifications": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"ExecutiveType": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Education": {
"UnweightedScore": 0,
"ExpectedEducation": "",
"ActualEducation": "",
"Comparison": "",
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Taxonomies": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"ActualTaxonomies": {
"Primary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
},
"Secondary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
}
},
"DesiredTaxonomies": {
"Primary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
},
"Secondary": {
"Taxonomy": {
"Name": "",
"Id": "",
"Matched": false
},
"SubTaxnomy": {
"Name": "",
"Id": "",
"Matched": false
}
}
}
},
"JobTitles": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Found": [
{
"RawTerm": "",
"VariationOf": "",
"IsCurrent": false
}
],
"NotFound": [
""
]
},
"Skills": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Found": [
{
"Skill": "",
"IsCurrent": false
}
],
"NotFound": [
""
]
},
"ManagementLevel": {
"UnweightedScore": 0,
"Evidence": [
{
"Fact": "",
"Type": ""
}
],
"Actual": "",
"Desired": "",
"AmountOfExperienceMatches": false
}
},
"EnrichedRCSScoreData": {
"Languages": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Certifications": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"ExecutiveType": {
"UnweightedScore": 0,
"Found": [
""
],
"NotFound": [
""
],
"Evidence": [
{
"Fact": "",
"Type": ""
}
]
},
"Education": {
"UnweightedScore": 0,
"ExpectedEducation": "",
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