Word counts may be returned with extensive details. For example by these methods:
PROPERTIES
The payload properties are:
date | The date when the counts were assigned. | datetime |
general | General word count details. This is the information that you would see in the typical Wordbee Translator word count pages. See below for more details. | object |
words | Counts in terms of words. This includes all the counts from general that strictly refer to words. | object |
chars | Counts in terms of chars. This is the extrapolation of counts in terms of characters. Basically, we take all the numbers from words multiplied with the total characters and divided by the total words. | object |
intervals | An array with the lower and upper limits of the fuzzy intervals to apply. Example when a word count profile defines 2 intervals: [
{
"min": 110,
"max": 110
},
{
"min": 100,
"max": 95
}
]
| object[] |
The general object has these properties:
total | Total number | int |
chars | Total characters | int |
pages | Total pages. Null if not supplied. | int? |
minutes | Total minutes. Null if not supplied. | int? |
wordsExcluded | Words excluded from the counts. | int |
charsTranslated | Total translated characters. Null if not calculated. | int? |
wordsTranslated | Total translated words. Null if not calculated. | int? |
Pretranslated words | ||
wdPretransIdentical | Total pretranslated words, whether pretranslations are 100%, 110% or MT. | int |
wdPretransIdenticalCtx | Among wdPretransIdentical, the 110% pretranslated words. Also called perfect or in-context match. | int |
wdPretransIdenticalPrevCtx | Among wdPretransIdentical, the 110% pretranslated words, leveraged from the previous document version. | int |
wdPretransIdenticalPrev | Among wdPretransIdentical, the 100% pretranslated words, leveraged from the previous document version. | int |
wdPretransIdenticalMT | Among wdPretransIdentical, the machine translated words | int |
wdPretransFuzzy | <100% pretranslated words | int |
wd110 | Total of 110% pretranslations. Equals sum of wdPretransIdenticalCtx + wdPretransIdenticalPrevCtx | int |
wd100 | Total of 100% pretranslations. Equals wdPretransIdentical - wdPretransIdenticalCtx - wdPretransIdenticalPrevCtx | int |
Fuzzy matches (not used for pre-translation) and repetitions | ||
wdMatch1 | Total words falling into interval #1. The intervals (minimum % to maximum %) are configured in the project word count profile. | int |
wdMatch2 | Total words falling into interval #2. | int |
wdMatch3 | Total words falling into interval #3. | int |
wdMatch4 | Total words falling into interval #4. | int |
wdMatch5 | Total words falling into interval #5. | int |
Advanced | ||
tags | Total amount of markup | int |
spaces | Total count of whitespace characters | int |
punctuation | Total punctuation characters | int |
nonAsianWords | Total non-Asian words | int |
asianCharacters | Total Asian characters (Japanese, Chinese, Korean signs) | int |
The words and chars objects contain the counts in terms of words and characters, respectively:
segments | Total segments | int |
words | Total words | int |
chars | Total characters | int |
pages | Total pages. Null if not supplied. | int? |
minutes | Total minutes. Null if not supplied. | int? |
wordsExcluded | Words excluded from the counts. | int |
charsTranslated | Total translated characters. Null if not calculated. | int? |
wordsTranslated | Total translated words. Null if not calculated. | int? |
Pretranslated words | ||
wdPretransIdentical | Total pretranslated words, whether pretranslations are 100%, 110% or MT. | int |
wdPretransIdenticalCtx | Among wdPretransIdentical, the 110% pretranslated words. Also called perfect or in-context match. | int |
wdPretransIdenticalPrevCtx | Among wdPretransIdentical, the 110% pretranslated words, leveraged from the previous document version. | int |
wdPretransIdenticalPrev | Among wdPretransIdentical, the 100% pretranslated words, leveraged from the previous document version. | int |
wdPretransIdenticalMT | Among wdPretransIdentical, the machine translated words | int |
wdPretransFuzzy | <100% pretranslated words | int |
wd110 | Total of 110% pretranslations. Equals sum of wdPretransIdenticalCtx + wdPretransIdenticalPrevCtx | int |
wd100 | Total of 100% pretranslations. Equals wdPretransIdentical - wdPretransIdenticalCtx - wdPretransIdenticalPrevCtx | int |
Fuzzy matches (not used for pre-translation) and repetitions | ||
wdMatch1 | Total words falling into interval #1. The intervals (minimum % to maximum %) are configured in the project word count profile. | int |
wdMatch2 | Total words falling into interval #2. | int |
wdMatch3 | Total words falling into interval #3. | int |
wdMatch4 | Total words falling into interval #4. | int |
wdMatch5 | Total words falling into interval #5. | int |
Advanced | ||
tags | Total amount of markup | int |
spaces | Total count of whitespace characters | int |
punctuation | Total punctuation characters | int |
nonAsianWords | Total non-Asian words | int |
asianCharacters | Total Asian characters (Japanese, Chinese, Korean signs) | int |
EXAMPLES
To clarify how reductions, fees and coverage are applied on the base cost, see this screenshot and the corresponding payload below:
"cost": {
"total": 495.00,
"totalBase": 1000.00,
"reduction": {
"amount": 100.00,
"percent": 10.0,
"subTotal": 900.00
},
"fee": {
"amount": 90.00,
"percent": 10.0,
"subTotal": 990.00
},
"covered": {
"percent": 50.0,
"subTotal": 495.00
},
"currency": "USD",
"decimals": 2
}