3.0.0 • Published 5 years ago

@datafire/namsor v3.0.0

Weekly downloads
1
License
MIT
Repository
github
Last release
5 years ago

@datafire/namsor

Client library for NamSor API v2

Installation and Usage

npm install --save @datafire/namsor
let namsor = require('@datafire/namsor').create({
  api_key: ""
});

.then(data => {
  console.log(data);
});

Description

NamSor API v2 : enpoints to process personal names (gender, cultural origin or ethnicity) in all alphabets or languages. Use GET methods for small tests, but prefer POST methods for higher throughput (batch processing of up to 100 names at a time). Need something you can't find here? We have many more features coming soon. Let us know, we'll do our best to add it!

Actions

addCredits

Add usage credits to an API Key.

namsor.addCredits({
  "apiKey": "",
  "usageCredits": 0,
  "userMessage": ""
}, context)

Input

  • input object
    • apiKey required string
    • usageCredits required integer
    • userMessage required string

Output

anonymize

Activate/deactivate anonymization for a source.

namsor.anonymize({
  "source": "",
  "anonymized": true
}, context)

Input

  • input object
    • source required string
    • anonymized required boolean

Output

Output schema unknown

availableServices

List of API services and usage cost in Units (default is 1=ONE Unit).

namsor.availableServices(null, context)

Input

This action has no parameters

Output

apiStatus

Prints the current status of the classifiers.

namsor.apiStatus(null, context)

Input

This action has no parameters

Output

apiUsage

Print current API usage.

namsor.apiUsage(null, context)

Input

This action has no parameters

Output

apiUsageHistory

Print historical API usage.

namsor.apiUsageHistory(null, context)

Input

This action has no parameters

Output

apiUsageHistoryAggregate

Print historical API usage (in an aggregated view, by service, by day/hour/min).

namsor.apiUsageHistoryAggregate(null, context)

Input

This action has no parameters

Output

availablePlans

List all available plans in the default currency (usd).

namsor.availablePlans(null, context)

Input

This action has no parameters

Output

availablePlans_1

List all available plans in the user's preferred currency.

namsor.availablePlans_1({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

billingCurrencies

List possible currency options for billing (USD, EUR, GBP, ...)

namsor.billingCurrencies(null, context)

Input

This action has no parameters

Output

billingHistory

Read the history billing information (invoices paid via Stripe or manually).

namsor.billingHistory({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

billingInfo

Read the billing information (company name, address, phone, vat ID)

namsor.billingInfo({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

charge

Create a Stripe Customer, based on a payment card token (from secure StripeJS) and email.

namsor.charge({}, context)

Input

  • input object
    • body object
      • stripeEmail string
      • stripeToken string

Output

chineseNameCandidates

Identify Chinese name candidates, based on the romanized name ex. Wang Xiaoming

namsor.chineseNameCandidates({
  "chineseSurnameLatin": "",
  "chineseGivenNameLatin": ""
}, context)

Input

  • input object
    • chineseSurnameLatin required string
    • chineseGivenNameLatin required string

Output

chineseNameCandidatesBatch

Identify Chinese name candidates, based on the romanized name (firstName = chineseGivenName; lastName=chineseSurname), ex. Wang Xiaoming

namsor.chineseNameCandidatesBatch({}, context)

Input

Output

chineseNameCandidatesGenderBatch

Identify Chinese name candidates, based on the romanized name (firstName = chineseGivenName; lastName=chineseSurname) ex. Wang Xiaoming.

namsor.chineseNameCandidatesGenderBatch({}, context)

Input

Output

chineseNameGenderCandidates

Identify Chinese name candidates, based on the romanized name ex. Wang Xiaoming - having a known gender ('male' or 'female')

namsor.chineseNameGenderCandidates({
  "chineseSurnameLatin": "",
  "chineseGivenNameLatin": "",
  "knownGender": ""
}, context)

Input

  • input object
    • chineseSurnameLatin required string
    • chineseGivenNameLatin required string
    • knownGender required string

Output

chineseNameMatch

Return a score for matching Chinese name ex. 王晓明 with a romanized name ex. Wang Xiaoming

namsor.chineseNameMatch({
  "chineseSurnameLatin": "",
  "chineseGivenNameLatin": "",
  "chineseName": ""
}, context)

Input

  • input object
    • chineseSurnameLatin required string
    • chineseGivenNameLatin required string
    • chineseName required string

Output

chineseNameMatchBatch

Identify Chinese name candidates, based on the romanized name (firstName = chineseGivenName; lastName=chineseSurname), ex. Wang Xiaoming

namsor.chineseNameMatchBatch({}, context)

Input

Output

corporateKey

Setting an API Key to a corporate status.

namsor.corporateKey({
  "apiKey": "",
  "corporate": true
}, context)

Input

  • input object
    • apiKey required string
    • corporate required boolean

Output

Output schema unknown

country

USES 10 UNITS PER NAME Infer the likely country of residence of a personal full name, or one surname. Assumes names as they are in the country of residence OR the country of origin.

namsor.country({
  "personalNameFull": ""
}, context)

Input

  • input object
    • personalNameFull required string

Output

countryBatch

USES 10 UNITS PER NAME Infer the likely country of residence of up to 100 personal full names, or surnames. Assumes names as they are in the country of residence OR the country of origin.

namsor.countryBatch({}, context)

Input

Output

debugLevel

Update debug level for a classifier

namsor.debugLevel({
  "logger": "",
  "level": ""
}, context)

Input

  • input object
    • logger required string
    • level required string

Output

Output schema unknown

diaspora

USES 20 UNITS PER NAME Infer the likely ethnicity/diaspora of a personal name, given a country of residence ISO2 code (ex. US, CA, AU, NZ etc.)

namsor.diaspora({
  "countryIso2": "",
  "firstName": "",
  "lastName": ""
}, context)

Input

  • input object
    • countryIso2 required string
    • firstName required string
    • lastName required string

Output

diasporaBatch

USES 20 UNITS PER NAME Infer the likely ethnicity/diaspora of up to 100 personal names, given a country of residence ISO2 code (ex. US, CA, AU, NZ etc.)

namsor.diasporaBatch({}, context)

Input

Output

flush

Flush counters.

namsor.flush(null, context)

Input

This action has no parameters

Output

Output schema unknown

gender

Infer the likely gender of a name.

namsor.gender({
  "firstName": "",
  "lastName": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string

Output

genderBatch

Infer the likely gender of up to 100 names, detecting automatically the cultural context.

namsor.genderBatch({}, context)

Input

Output

genderChineseName

Infer the likely gender of a Chinese full name ex. 王晓明

namsor.genderChineseName({
  "chineseName": ""
}, context)

Input

  • input object
    • chineseName required string

Output

genderChineseNameBatch

Infer the likely gender of up to 100 full names ex. 王晓明

namsor.genderChineseNameBatch({}, context)

Input

Output

genderChineseNamePinyin

Infer the likely gender of a Chinese name in LATIN (Pinyin).

namsor.genderChineseNamePinyin({
  "chineseSurnameLatin": "",
  "chineseGivenNameLatin": ""
}, context)

Input

  • input object
    • chineseSurnameLatin required string
    • chineseGivenNameLatin required string

Output

genderChineseNamePinyinBatch

Infer the likely gender of up to 100 Chinese names in LATIN (Pinyin).

namsor.genderChineseNamePinyinBatch({}, context)

Input

Output

genderFull

Infer the likely gender of a full name, ex. John H. Smith

namsor.genderFull({
  "fullName": ""
}, context)

Input

  • input object
    • fullName required string

Output

genderFullBatch

Infer the likely gender of up to 100 full names, detecting automatically the cultural context.

namsor.genderFullBatch({}, context)

Input

Output

genderFullGeo

Infer the likely gender of a full name, given a local context (ISO2 country code).

namsor.genderFullGeo({
  "fullName": "",
  "countryIso2": ""
}, context)

Input

  • input object
    • fullName required string
    • countryIso2 required string

Output

genderFullGeoBatch

Infer the likely gender of up to 100 full names, with a given cultural context (country ISO2 code).

namsor.genderFullGeoBatch({}, context)

Input

Output

genderGeo

Infer the likely gender of a name, given a local context (ISO2 country code).

namsor.genderGeo({
  "firstName": "",
  "lastName": "",
  "countryIso2": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string
    • countryIso2 required string

Output

genderGeoBatch

Infer the likely gender of up to 100 names, each given a local context (ISO2 country code).

namsor.genderGeoBatch({}, context)

Input

Output

genderJapaneseNamePinyin

Infer the likely gender of a Japanese name in LATIN (Pinyin).

namsor.genderJapaneseNamePinyin({
  "japaneseSurname": "",
  "japaneseGivenName": ""
}, context)

Input

  • input object
    • japaneseSurname required string
    • japaneseGivenName required string

Output

genderJapaneseNamePinyinBatch

Infer the likely gender of up to 100 Japanese names in LATIN (Pinyin).

namsor.genderJapaneseNamePinyinBatch({}, context)

Input

Output

genderJapaneseNameFull

Infer the likely gender of a Japanese full name ex. 王晓明

namsor.genderJapaneseNameFull({
  "japaneseName": ""
}, context)

Input

  • input object
    • japaneseName required string

Output

genderJapaneseNameFullBatch

Infer the likely gender of up to 100 full names

namsor.genderJapaneseNameFullBatch({}, context)

Input

Output

invalidateCache

Invalidate system caches.

namsor.invalidateCache(null, context)

Input

This action has no parameters

Output

Output schema unknown

japaneseNameKanjiCandidates

Identify japanese name candidates in KANJI, based on the romanized name ex. Yamamoto Sanae

namsor.japaneseNameKanjiCandidates({
  "japaneseSurnameLatin": "",
  "japaneseGivenNameLatin": ""
}, context)

Input

  • input object
    • japaneseSurnameLatin required string
    • japaneseGivenNameLatin required string

Output

japaneseNameKanjiCandidatesBatch

Identify japanese name candidates in KANJI, based on the romanized name (firstName = japaneseGivenName; lastName=japaneseSurname), ex. Yamamoto Sanae

namsor.japaneseNameKanjiCandidatesBatch({}, context)

Input

Output

japaneseNameLatinCandidates

Romanize japanese name, based on the name in Kanji.

namsor.japaneseNameLatinCandidates({
  "japaneseSurnameKanji": "",
  "japaneseGivenNameKanji": ""
}, context)

Input

  • input object
    • japaneseSurnameKanji required string
    • japaneseGivenNameKanji required string

Output

japaneseNameLatinCandidatesBatch

Romanize japanese names, based on the name in KANJI

namsor.japaneseNameLatinCandidatesBatch({}, context)

Input

Output

japaneseNameMatch

Return a score for matching Japanese name in KANJI ex. 山本 早苗 with a romanized name ex. Yamamoto Sanae

namsor.japaneseNameMatch({
  "japaneseSurnameLatin": "",
  "japaneseGivenNameLatin": "",
  "japaneseName": ""
}, context)

Input

  • input object
    • japaneseSurnameLatin required string
    • japaneseGivenNameLatin required string
    • japaneseName required string

Output

japaneseNameMatchBatch

Return a score for matching a list of Japanese names in KANJI ex. 山本 早苗 with romanized names ex. Yamamoto Sanae

namsor.japaneseNameMatchBatch({}, context)

Input

Output

japaneseNameMatchFeedbackLoop

CREDITS 1 UNIT Feedback loop to better perform matching Japanese name in KANJI ex. 山本 早苗 with a romanized name ex. Yamamoto Sanae

namsor.japaneseNameMatchFeedbackLoop({
  "japaneseSurnameLatin": "",
  "japaneseGivenNameLatin": "",
  "japaneseName": ""
}, context)

Input

  • input object
    • japaneseSurnameLatin required string
    • japaneseGivenNameLatin required string
    • japaneseName required string

Output

learnable

Activate/deactivate learning from a source.

namsor.learnable({
  "source": "",
  "learnable": true
}, context)

Input

  • input object
    • source required string
    • learnable required boolean

Output

Output schema unknown

namsorCounter

Get the overall API counter

namsor.namsorCounter(null, context)

Input

This action has no parameters

Output

origin

USES 10 UNITS PER NAME Infer the likely country of origin of a personal name. Assumes names as they are in the country of origin. For US, CA, AU, NZ and other melting-pots : use 'diaspora' instead.

namsor.origin({
  "firstName": "",
  "lastName": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string

Output

originBatch

USES 10 UNITS PER NAME Infer the likely country of origin of up to 100 names, detecting automatically the cultural context.

namsor.originBatch({}, context)

Input

Output

parseChineseName

Infer the likely first/last name structure of a name, ex. 王晓明 -> 王(surname) 晓明(given name)

namsor.parseChineseName({
  "chineseName": ""
}, context)

Input

  • input object
    • chineseName required string

Output

parseChineseNameBatch

Infer the likely first/last name structure of a name, ex. 王晓明 -> 王(surname) 晓明(given name).

namsor.parseChineseNameBatch({}, context)

Input

Output

parseJapaneseName

Infer the likely first/last name structure of a name, ex. 山本 早苗 or Yamamoto Sanae

namsor.parseJapaneseName({
  "japaneseName": ""
}, context)

Input

  • input object
    • japaneseName required string

Output

parseJapaneseNameBatch

Infer the likely first/last name structure of a name, ex. 山本 早苗 or Yamamoto Sanae 

namsor.parseJapaneseNameBatch({}, context)

Input

Output

parseName

Infer the likely first/last name structure of a name, ex. John Smith or SMITH, John or SMITH; John. 

namsor.parseName({
  "nameFull": ""
}, context)

Input

  • input object
    • nameFull required string

Output

parseNameGeo

Infer the likely first/last name structure of a name, ex. John Smith or SMITH, John or SMITH; John. For better accuracy, provide a geographic context.

namsor.parseNameGeo({
  "nameFull": "",
  "countryIso2": ""
}, context)

Input

  • input object
    • nameFull required string
    • countryIso2 required string

Output

parseNameBatch

Infer the likely first/last name structure of a name, ex. John Smith or SMITH, John or SMITH; John.

namsor.parseNameBatch({}, context)

Input

Output

parseNameGeoBatch

Infer the likely first/last name structure of a name, ex. John Smith or SMITH, John or SMITH; John. Giving a local context improves precision. 

namsor.parseNameGeoBatch({}, context)

Input

Output

parsedGenderBatch

Infer the likely gender of up to 100 fully parsed names, detecting automatically the cultural context.

namsor.parsedGenderBatch({}, context)

Input

Output

parsedGenderGeoBatch

Infer the likely gender of up to 100 fully parsed names, detecting automatically the cultural context.

namsor.parsedGenderGeoBatch({}, context)

Input

Output

paymentInfo

Get the Stripe payment information associated with the current google auth session token.

namsor.paymentInfo({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

phoneCode

USES 11 UNITS PER NAME Infer the likely country and phone prefix, given a personal name and formatted / unformatted phone number.

namsor.phoneCode({
  "firstName": "",
  "lastName": "",
  "phoneNumber": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string
    • phoneNumber required string

Output

phoneCodeBatch

USES 11 UNITS PER NAME Infer the likely country and phone prefix, of up to 100 personal names, detecting automatically the local context given a name and formatted / unformatted phone number.

namsor.phoneCodeBatch({}, context)

Input

Output

phoneCodeGeo

USES 11 UNITS PER NAME Infer the likely phone prefix, given a personal name and formatted / unformatted phone number, with a local context (ISO2 country of residence).

namsor.phoneCodeGeo({
  "firstName": "",
  "lastName": "",
  "phoneNumber": "",
  "countryIso2": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string
    • phoneNumber required string
    • countryIso2 required string

Output

phoneCodeGeoBatch

USES 11 UNITS PER NAME Infer the likely country and phone prefix, of up to 100 personal names, with a local context (ISO2 country of residence).

namsor.phoneCodeGeoBatch({}, context)

Input

Output

phoneCodeGeoFeedbackLoop

CREDITS 1 UNIT Feedback loop to better infer the likely phone prefix, given a personal name and formatted / unformatted phone number, with a local context (ISO2 country of residence).

namsor.phoneCodeGeoFeedbackLoop({
  "firstName": "",
  "lastName": "",
  "phoneNumber": "",
  "phoneNumberE164": "",
  "countryIso2": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string
    • phoneNumber required string
    • phoneNumberE164 required string
    • countryIso2 required string

Output

pinyinChineseName

Romanize the Chinese name to Pinyin, ex. 王晓明 -> Wang (surname) Xiaoming (given name)

namsor.pinyinChineseName({
  "chineseName": ""
}, context)

Input

  • input object
    • chineseName required string

Output

pinyinChineseNameBatch

Romanize a list of Chinese name to Pinyin, ex. 王晓明 -> Wang (surname) Xiaoming (given name).

namsor.pinyinChineseNameBatch({}, context)

Input

Output

procureKey

Procure an API Key (sent via Email), based on an auth token. Keep your API Key secret.

namsor.procureKey({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

redeployUI

Redeploy UI from current dev branch.

namsor.redeployUI(null, context)

Input

This action has no parameters

Output

Output schema unknown

redeployUI_1

Redeploy UI from current dev branch.

namsor.redeployUI_1({
  "live": true
}, context)

Input

  • input object
    • live required boolean

Output

Output schema unknown

removeUserAccount

Remove the user account.

namsor.removeUserAccount({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

removeUserAccountOnBehalf

Remove (on behalf) a user account.

namsor.removeUserAccountOnBehalf({
  "apiKey": ""
}, context)

Input

  • input object
    • apiKey required string

Output

shutdown

Stop learning and shutdown system.

namsor.shutdown(null, context)

Input

This action has no parameters

Output

Output schema unknown

softwareVersion

Get the current software version

namsor.softwareVersion(null, context)

Input

This action has no parameters

Output

sourceStats

Print basic source statistics.

namsor.sourceStats({
  "source": ""
}, context)

Input

  • input object
    • source required string

Output

stats

Print basic system statistics.

namsor.stats(null, context)

Input

This action has no parameters

Output

stripeConnect

Connects a Stripe Account.

namsor.stripeConnect({}, context)

Input

  • input object
    • scope string
    • code string
    • error string
    • error_description string

Output

Output schema unknown

subscribePlan

Subscribe to a give API plan, using the user's preferred or default currency.

namsor.subscribePlan({
  "planName": "",
  "token": ""
}, context)

Input

  • input object
    • planName required string
    • token required string

Output

subscribePlanOnBehalf

Subscribe to a give API plan, using the user's preferred or default currency (admin only).

namsor.subscribePlanOnBehalf({
  "planName": "",
  "apiKey": ""
}, context)

Input

  • input object
    • planName required string
    • apiKey required string

Output

taxonomyClasses

Print the taxonomy classes valid for the given classifier.

namsor.taxonomyClasses({
  "classifierName": ""
}, context)

Input

  • input object
    • classifierName required string

Output

updateBillingInfo

Sets or update the billing information (company name, address, phone, vat ID)

namsor.updateBillingInfo({
  "token": ""
}, context)

Input

Output

updateLimit

Modifies the hard/soft limit on the API plan's overages (default is 0$ soft limit).

namsor.updateLimit({
  "usageLimit": 0,
  "hardOrSoft": true,
  "token": ""
}, context)

Input

  • input object
    • usageLimit required integer
    • hardOrSoft required boolean
    • token required string

Output

updatePaymentDefault

Update the default Stripe card associated with the current google auth session token.

namsor.updatePaymentDefault({
  "defautSourceId": "",
  "token": ""
}, context)

Input

  • input object
    • defautSourceId required string
    • token required string

Output

usRaceEthnicity

USES 10 UNITS PER NAME Infer a US resident's likely race/ethnicity according to US Census taxonomy W_NL (white, non latino), HL (hispano latino), A (asian, non latino), B_NL (black, non latino).

namsor.usRaceEthnicity({
  "firstName": "",
  "lastName": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string

Output

usRaceEthnicityBatch

USES 10 UNITS PER NAME Infer up-to 100 US resident's likely race/ethnicity according to US Census taxonomy.

namsor.usRaceEthnicityBatch({}, context)

Input

Output

usRaceEthnicityZIP5

USES 10 UNITS PER NAME Infer a US resident's likely race/ethnicity according to US Census taxonomy, using (optional) ZIP5 code info. Output is W_NL (white, non latino), HL (hispano latino), A (asian, non latino), B_NL (black, non latino).

namsor.usRaceEthnicityZIP5({
  "firstName": "",
  "lastName": "",
  "zip5Code": ""
}, context)

Input

  • input object
    • firstName required string
    • lastName required string
    • zip5Code required string

Output

usZipRaceEthnicityBatch

USES 10 UNITS PER NAME Infer up-to 100 US resident's likely race/ethnicity according to US Census taxonomy, with (optional) ZIP code.

namsor.usZipRaceEthnicityBatch({}, context)

Input

Output

userInfo

Get the user profile associated with the current google auth session token.

namsor.userInfo({
  "token": ""
}, context)

Input

  • input object
    • token required string

Output

verifyEmail

Verifies an email, based on token sent to that email

namsor.verifyEmail({
  "emailToken": ""
}, context)

Input

  • input object
    • emailToken required string

Output

verifyRemoveEmail

Verifies an email, based on token sent to that email

namsor.verifyRemoveEmail({
  "emailToken": ""
}, context)

Input

  • input object
    • emailToken required string

Output

vet

Vetting of a source.

namsor.vet({
  "source": "",
  "vetted": true
}, context)

Input

  • input object
    • source required string
    • vetted required boolean

Output

Output schema unknown

Definitions

APIBillingPeriodUsageOut

  • APIBillingPeriodUsageOut object
    • apiKey string
    • billingStatus string
    • hardLimit integer
    • periodEnded integer
    • periodStarted integer
    • softLimit integer
    • stripeCurrentPeriodEnd integer
    • stripeCurrentPeriodStart integer
    • subscriptionStarted integer
    • usage integer

APIClassifierOut

  • APIClassifierOut object
    • classifierName string
    • learning boolean
    • probabilityCalibrated boolean
    • serving boolean
    • shuttingDown boolean

APIClassifierTaxonomyOut

  • APIClassifierTaxonomyOut object
    • classifierName string
    • taxonomyClasses array
      • items string

APIClassifiersStatusOut

APICounterV2Out

  • APICounterV2Out object
    • apiKey APIKeyOut
    • apiService string
    • createdDateTime integer
    • lastFlushedDateTime integer
    • lastUsedDateTime integer
    • serviceFeaturesUsage object
    • totalUsage integer

APIKeyOut

  • APIKeyOut object
    • admin boolean
    • anonymized boolean
    • apiKey string
    • corporate boolean
    • disabled boolean
    • learnable boolean
    • partner boolean
    • striped boolean
    • userId string
    • vetted boolean

APIPeriodUsageOut

APIPlanOut

  • APIPlanOut object
    • planName string
    • planQuota integer
    • price number
    • priceOverage number

APIPlanSubscriptionOut

  • APIPlanSubscriptionOut object
    • apiKey string
    • currency string
    • currencyFactor number
    • planBaseFeesKey string
    • planEnded integer
    • planName string
    • planQuota integer
    • planStarted integer
    • planStatus string
    • price number
    • priceOverage number
    • priceOverageUSD number
    • priceUSD number
    • priorPlanStarted integer
    • stripeCustomerId string
    • stripeStatus string
    • stripeSubscription string
    • taxRate number
    • userId string

APIPlansOut

  • APIPlansOut object
    • currencyIso3 string
    • currencySymbol string
    • plans array
    • usageRatioForDupplicates integer

APIServiceOut

  • APIServiceOut object
    • costInUnits integer
    • serviceGroup string
    • serviceName string

APIServicesOut

APIUsageAggregatedOut

  • APIUsageAggregatedOut object
    • colHeaders array
      • items string
    • data array
      • items array
        • items integer
    • historyTruncated boolean
    • periodEnd integer
    • periodStart integer
    • rowHeaders array
      • items string
    • timeUnit string
    • totalUsage integer

BatchFirstLastNameDiasporaedOut

  • BatchFirstLastNameDiasporaedOut object: Represents the output of inferring the LIKELY ethnicity from a personal name, given an country of residence.

BatchFirstLastNameGenderIn

BatchFirstLastNameGenderedOut

  • BatchFirstLastNameGenderedOut object: Represents the output of inferring the LIKELY gender from a list of personal names.

BatchFirstLastNameGeoIn

BatchFirstLastNameGeoZippedIn

BatchFirstLastNameIn

BatchFirstLastNameOriginedOut

  • BatchFirstLastNameOriginedOut object: Represents the output of inferring the LIKELY origin from a list of personal names.

BatchFirstLastNamePhoneCodedOut

  • BatchFirstLastNamePhoneCodedOut object: Represents the output of inferring the LIKELY country and phone code of personal names+phones.

BatchFirstLastNamePhoneNumberGeoIn

BatchFirstLastNamePhoneNumberIn

BatchFirstLastNameUSRaceEthnicityOut

  • BatchFirstLastNameUSRaceEthnicityOut object: Represents the output of inferring the LIKELY US 'race/ethnicity' from a personal name, given US country of residence and (optionally) a ZIP5 code.

BatchMatchPersonalFirstLastNameIn

BatchNameMatchCandidatesOut

BatchNameMatchedOut

BatchParsedFullNameGeoIn

BatchParsedFullNameIn

BatchPersonalNameGenderedOut

BatchPersonalNameGeoIn

BatchPersonalNameGeoOut

BatchPersonalNameIn

BatchPersonalNameParsedOut

BillingHistoryOut

BillingInfoInOut

  • BillingInfoInOut object
    • addressCity string
    • addressCountry string
    • addressLine1 string
    • addressLine2 string
    • addressPostalCode string
    • addressState string
    • billingEmail string
    • customerName string
    • customerPhone string
    • preferredCurrency string
    • vatID string

CacheMetricsOut

  • CacheMetricsOut object: Simple metrics system caches
    • cacheName string
    • cacheStats string

ClassifierMetricsOut

  • ClassifierMetricsOut object: Simple metrics on a classifier
    • aiNonVettedEstimatePrecision number
    • aiNonVettedEstimateRecall number
    • aiNonVettedEstimateTotal integer
    • aiNonVettedExpectedClassMetrics array
    • aiNonVettedLearnTotal integer
    • aiStartTime integer
    • aiVettedEstimatePrecision number
    • aiVettedEstimateRecall number
    • aiVettedEstimateTotal integer
    • aiVettedExpectedClassMetrics array
    • aiVettedLearnTotal integer
    • bufferSize integer
    • classifierName string
    • classifyDurationsCurrent number
    • classifyDurationsSummary number
    • factKeysSize integer
    • factsLearned integer
    • featuresSize integer
    • hostAddress string
    • learnDurationsCurrent number
    • learnDurationsSummary number
    • learnQueueSize integer
    • metricTimeStamp integer
    • preClassifyQueueSize integer
    • softwareVersion string

CurrenciesOut

  • CurrenciesOut object
    • currenciesIso3 array
      • items string

DeployUIOut

  • DeployUIOut object
    • errorMessage string
    • succeeded boolean

ExpectedClassMetricsOut

  • ExpectedClassMetricsOut object: Simple metrics on a classifier, for a given expected class
    • aiEstimatePrecision number
    • aiEstimateRecall number
    • aiEstimateTotal integer
    • aiLearnTotal integer
    • classifierName string
    • expectedClass string

FeedbackLoopOut

  • FeedbackLoopOut object
    • feedbackCredits integer

FirstLastNameDiasporaedOut

  • FirstLastNameDiasporaedOut object: Represents the output of inferring the LIKELY ethnicity from a personal name, given an country of residence.
    • countryIso2 string
    • ethnicitiesTop array: List ethnicities (top 10)
      • items string: List ethnicities (top 10)
    • ethnicity string
    • ethnicityAlt string
    • firstName string
    • id string
    • lastName string
    • lifted boolean
    • score number: Compatibility to NamSor_v1 Origin score value

FirstLastNameGenderIn

  • FirstLastNameGenderIn object
    • firstName string
    • gender string
    • id string
    • lastName string

FirstLastNameGenderedOut

  • FirstLastNameGenderedOut object: Represents the output of inferring the LIKELY gender from a personal name.
    • firstName string
    • genderScale number: Compatibility to NamSor_v1 Gender Scale M-1..U..+1F value
    • id string
    • lastName string
    • likelyGender string (values: male, female, unknown): Most likely gender
    • probabilityCalibrated number
    • score number

FirstLastNameGeoIn

  • FirstLastNameGeoIn object
    • countryIso2 string
    • firstName string
    • id string
    • lastName string

FirstLastNameGeoZippedIn

  • FirstLastNameGeoZippedIn object
    • countryIso2 string
    • firstName string
    • id string
    • lastName string
    • zipCode string

FirstLastNameIn

  • FirstLastNameIn object
    • firstName string
    • id string
    • lastName string

FirstLastNameOriginedOut

  • FirstLastNameOriginedOut object: Represents the output of inferring the LIKELY country of Origin from a personal name.
    • countriesOriginTop array: List countries of Origin (top 10)
      • items string: List countries of Origin (top 10)
    • countryOrigin string: Most likely country of Origin
    • countryOriginAlt string: Second best alternative : country of Origin
    • firstName string
    • id string
    • lastName string
    • probabilityAltCalibrated number
    • probabilityCalibrated number
    • regionOrigin string: Most likely region of Origin (based on countryOrigin ISO2 code)
    • score number: Compatibility to NamSor_v1 Origin score value
    • subRegionOrigin string: Most likely region of Origin (based on countryOrigin ISO2 code)
    • topRegionOrigin string: Most likely region of Origin (based on countryOrigin ISO2 code)

FirstLastNameOut

  • FirstLastNameOut object
    • firstName string
    • id string
    • lastName string

FirstLastNamePhoneCodedOut

  • FirstLastNamePhoneCodedOut object: Represents the output of inferring the LIKELY country and phone code from a personal name and phone number.
    • countryIso2 string
    • firstName string
    • id string
    • internationalPhoneNumberVerified string
    • lastName string
    • originCountryIso2 string
    • originCountryIso2Alt string
    • phoneCountryCode integer
    • phoneCountryCodeAlt integer
    • phoneCountryIso2 string
    • phoneCountryIso2Alt string
    • phoneCountryIso2Verified string
    • phoneNumber string
    • score number
    • verified boolean

FirstLastNamePhoneNumberGeoIn

  • FirstLastNamePhoneNumberGeoIn object
    • FirstLastNameOriginedOut FirstLastNameOriginedOut
    • countryIso2 string
    • countryIso2Alt string
    • firstName string
    • id string
    • lastName string
    • phoneNumber string

FirstLastNamePhoneNumberIn

  • FirstLastNamePhoneNumberIn object

FirstLastNameUSRaceEthnicityOut

  • FirstLastNameUSRaceEthnicityOut object: Represents the output of inferring the LIKELY US 'race/ethnicity' from a personal name, given US country of residence and (optionally) a ZIP5 code.
    • firstName string
    • id string
    • lastName string
    • probabilityAltCalibrated number
    • probabilityCalibrated number
    • raceEthnicitiesTop array: List 'race'/ethnicities
      • items string: List 'race'/ethnicities
    • raceEthnicity string (values: W_NL, HL, A, B_NL): Most likely US 'race'/ethnicity
    • raceEthnicityAlt string (values: W_NL, HL, A, B_NL): Second most likely US 'race'/ethnicity
    • score number: Compatibility to NamSor_v1 Origin score value

InvoiceItemOut

  • InvoiceItemOut object
    • amount integer
    • currency string
    • description string
    • invoiceItemType string
    • itemId string
    • planDesc string
    • planName string
    • planNickname string
    • quantity integer
    • subscription string
    • subscriptionItem string

InvoiceOut

  • InvoiceOut object
    • amountDue integer
    • amountPaid integer
    • amountRemaining integer
    • attempted boolean
    • currency string
    • description string
    • dueDate string
    • invoiceDate string
    • invoiceId string
    • invoicePdf string
    • invoiceStatus string
    • isStriped boolean
    • items array
    • periodEnd string
    • periodStart string
    • receiptNumber string
    • stripeCustomerId string
    • subTotal integer
    • tax integer
    • taxPercent integer
    • total integer
    • userId string

MatchPersonalFirstLastNameIn

NamSorCounterOut

  • NamSorCounterOut object
    • counter integer

NameMatchCandidateOut

  • NameMatchCandidateOut object
    • candidateName string
    • probability number

NameMatchCandidatesOut

  • NameMatchCandidatesOut object

NameMatchedOut

  • NameMatchedOut object
    • id string
    • matchStatus string
    • score number

ParsedFullNameGeoIn

  • ParsedFullNameGeoIn object
    • countryIso2 string
    • firstName string
    • id string
    • lastName string
    • middleName string
    • prefixOrTitle string
    • suffix string

ParsedFullNameIn

  • ParsedFullNameIn object
    • firstName string
    • id string
    • lastName string
    • middleName string
    • prefixOrTitle string
    • suffix string

PersonalNameGenderedOut

  • PersonalNameGenderedOut object
    • genderScale number: Compatibility to NamSor_v1 Gender Scale M-1..U..+1F value
    • id string
    • likelyGender string (values: male, female, unknown): Most likely gender
    • name string
    • probabilityCalibrated number
    • score number

PersonalNameGeoIn

  • PersonalNameGeoIn object
    • countryIso2 string
    • id string
    • name string

PersonalNameGeoOut

  • PersonalNameGeoOut object
    • countriesTop array: List countries (top 10)
      • items string: List countries (top 10)
    • country string
    • countryAlt string
    • id string
    • name string
    • probabilityAltCalibrated number
    • probabilityCalibrated number
    • region string
    • score number
    • subRegion string
    • topRegion string

PersonalNameIn

  • PersonalNameIn object
    • id string
    • name string

PersonalNameParsedOut

  • PersonalNameParsedOut object
    • firstLastName FirstLastNameOut
    • id string
    • name string
    • nameParserType string
    • nameParserTypeAlt string
    • score number

RomanizedNameOut

  • RomanizedNameOut object
    • id string
    • latinName string
    • originalName string
    • score number
    • sourceLanguage string
    • sourceScript string
    • targetLanguage string
    • targetScript string

SoftwareVersionOut

  • SoftwareVersionOut object
    • softwareNameAndVersion string
    • softwareVersion array
      • items integer

SourceDetailedMetricsOut

  • SourceDetailedMetricsOut object: Simple metrics on source, with details by classifier.
    • aiEstimatePrecision number
    • aiEstimateRecall number
    • aiEstimateTotal integer
    • aiLearnTotal integer
    • aiStartTime integer
    • classifierName string
    • expectedClassMetrics array
    • metricTimeStamp integer
    • snapshotDate integer
    • source APIKeyOut

SourceMetricsOut

  • SourceMetricsOut object: Simple metrics on a classifier, for a given source
    • aiEstimatePrecision number
    • aiEstimateRecall number
    • aiEstimateTotal integer
    • aiLearnTotal integer
    • aiStartTime integer
    • classifierName string
    • metricTimeStamp integer
    • snapshotDate integer
    • source APIKeyOut

StripeCardOut

  • StripeCardOut object
    • brand string
    • defaultCard boolean
    • expMonth integer
    • expYear integer
    • last4 string
    • sourceId string

StripeCustomerOut

  • StripeCustomerOut object
    • sourceCountry string
    • sourceCurrency string
    • stripeCustomerId string
    • stripedCards array

SystemMetricsOut

UserInfoOut

  • UserInfoOut object
    • apiKey string
    • disabled boolean
    • displayName string
    • email string
    • emailVerified boolean
    • firstKnownIpAddress string
    • otherInfos array
    • phoneNumber string
    • photoUrl string
    • providerId string
    • stripeCustomerId string
    • stripePerishableKey string
    • timeStamp integer
    • uid string
    • verifyToken string
datafire
@everything-registry/sub-chunk-222@infinitebrahmanuniverse/nolb-_datafire_n@zalastax/nolb-_datafire_n
3.0.0

5 years ago