Additional date formats to be considered during date obfuscation. This allows users to specify custom date formats in addition to the default dateFormats.

A map of age groups to obfuscate ages. For this parameter to be active, the obfuscateByAgeGroups parameter must be true. If the given ageGroups do not fully contain the ages, the ages continue to be obfuscated according to the ageRanges. The map should contain the age group name as the key and an array of two integers as the value. The first integer is the lower bound of the age group, and the second integer is the upper bound of the age group. Default age groups are as follows in the English language:

Map(
"baby" -> Array(0, 1),
"toddler" -> Array(1, 4),
"child" -> Array(4, 13),
"teenager" -> Array(13, 20),
"adult" -> Array(20, 65),
"senior" -> Array(65, 200)
)

List of integers specifying limits of the age groups to preserve during obfuscation

A Boolean variable indicating whether to obfuscate ages based on HIPAA (Health Insurance Portability and Accountability Act) Privacy Rule.

The HIPAA Privacy Rule mandates that ages from patients older than 90 years must be obfuscated, while age for patients 90 years or younger can remain unchanged.

When true, age entities larger than 90 will be obfuscated as per HIPAA Privacy Rule, the others will remain unchanged. When false, ageRanges parameter is valid.

List of entities that will be ignored in the regex file. The rest will be processed. The default values are "IBAN","ZIP","NPI","DLN","PASSPORT","C_CARD","DEA","SSN", "IP", "DEA".

List of entities coming from NER or regex rules that will be ignored for masking or obfuscation. The rest entities will be processed. Defaults to an empty array.

Performs entity chunk matching across rows or within groups in a DataFrame. Useful in de-identification pipelines where certain entity labels like "NAME" or "DATE" may be missing in some rows and need to be filled from other rows in the same group.

If the value is true both loaded regex file and default regex file are used together; if the value is false, either loaded regex file or default regex file is used. The default value is false If the value is true, it uses the default regex file regardless of the value of the regexOverride.

Param that indicates whether consistency should be enforced across different parts of a name (e.g., first name, middle name, last name). When set to true, the same transformation or obfuscation will be applied consistently to all parts of the same name entity, even if those parts appear separately.

For example, if "John Smith" is obfuscated as "Liam Brown", then:

• When the full name "John Smith" appears, it will be replaced with "Liam Brown"
• When "John" or "Smith" appear individually, they will still be obfuscated as "Liam" and "Brown" respectively, ensuring consistency in name transformation.

Default: true

Whether to replace very similar entities in a document with the same randomized term (default: true) The similarity is based on the Levenshtein Distance between the words.

Whether to obfuscate country entities or not. If true, country entities will be obfuscated using the Faker module. If false, country entities will be skipped during obfuscation. Default: false

List of date entities. Default: Array("DATE", "DOB", "DOD", "EFFDATE", "FISCAL_YEAR")

Format of dates to displace

Tag representing what are the NER entity (default: DATE)

true if dates must be converted to years, false otherwise

Number of days to obfuscate the dates by displacement. If not provided a random integer between 1 and 60 will be used

If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.

Whether to enable default obfuscation equivalents for common entities. This parameter allows the system to automatically include a set of predefined common English name equivalents. Default: false

Dictionary path where is the json that contains the entity casing modes. 'lowercase': Converts all characters to lower case using the rules of the default locale. 'uppercase': Converts all characters to upper case using the rules of the default locale. 'capitalize': Converts the first character to upper case and converts others to lower case. 'titlecase': Converts the first character in every token to upper case and converts others to lower case.

It specifies how much length deviation is accepted in obfuscation, with keepTextSizeForObfuscation enabled. Value must be greater than 0. Default is 3.

Select the fixed mask length: this is the length of the masking sequence that will be used when the 'fixed_length_chars' masking policy is selected.

Whether to use gender-aware names or not during obfuscation. This param effects only names. If value is true, it might decrease performance. Default: False

Whether to enforce consistent obfuscation across geographical entities: state, city, street, zip and phone.

## Functionality Overview This parameter enables intelligent geographical entity obfuscation that maintains realistic relationships between different geographic components. When enabled, the system ensures that obfuscated addresses form coherent, valid combinations rather than random replacements.

## Supported Entity Types The following geographical entities are processed with priority order: - **state** (Priority: 0) - US state names - **city** (Priority: 1) - City names - **zip** (Priority: 2) - Zip codes - **street** (Priority: 3) - Street addresses - **phone** (Priority: 4) - Phone numbers

## Language Requirement **IMPORTANT**: Geographic consistency is only applied when: - geoConsistency parameter is set to true AND - language parameter is set to en

For non-English configurations, this feature is automatically disabled regardless of the parameter setting.

## Consistency Algorithm When geographical entities comes from the chunk columns:

1. **Entity Grouping**: All geographic entities are identified and grouped by type 2. **Fake Address Selection**: A consistent set of fake US addresses is selected using hash-based deterministic selection to ensure reproducibility 3. **Priority-Based Mapping**: Entities are mapped to fake addresses following the priority order (state → city → zip → street → phone) 4. **Consistent Replacement**: All entities of the same type within a document use the same fake address pool, maintaining geographical coherence

## Parameter Interactions **IMPORTANT**: Enabling this parameter automatically disables: - keepTextSizeForObfuscation - Text size preservation is not maintained - consistentObfuscation - Standard consistency rules are overridden - file-based fakers

This is necessary because geographic consistency requires specific fake address selection that may not preserve original text lengths or follow standard obfuscation patterns.

default: false

Gets the value of additionalDateFormats

Gets ageRanges param.

Gets the value of ageRangesByHipaa.

Gets blackListEntities param

Gets the value of consistentAcrossNameParts.

Gets the value of countryObfuscation.

Gets dateEntities param.

Gets the value of dateFormats

Gets days param

Gets the value of enableDefaultObfuscationEquivalents.

Gets fakerLengthOffset param

Gets fixedMaskLength param.

Gets genderAwareness param.

Gets the value of geoConsistency.

Gets groupByCol param

Gets keepMonth param

Gets keepTextSizeForObfuscation param

Gets keepYear param

Gets language param.

Gets maskingPolicy param.

Gets metadataMaskingPolicy param

Gets mode param.

Gets obfuscateByAgeGroups param

Gets obfuscateDate param

Gets obfuscateRefSource param.

Gets the value of obfuscationEquivalents.

Gets region param.

Gets selectiveObfuscateRefSource param.

Gets selectiveObfuscationModes param.

Gets unnormalizedDateMode param.

Getter method of useShiftDays

Gets valid ageRanges whether ageRangesByHipaa is true or not.

The column name used to group the dataset. This parameter is used in conjunction with consistentObfuscation to ensure consistent obfuscation within each group. When groupByCol is set, the dataset is partitioned into groups based on the values of the specified column.

Default: "" (empty string, meaning no grouping)

• The column name must be a valid string in the input dataset.
• The column must be of StringType.

Select if you want to use regex file loaded in the model. If true the default regex file will be not used The default value is false.

Input annotator type: DOCUMENT, TOKEN, CHUNK

Use a random displacement days in dates entities,that random number is based on the DeIdentificationParams.seed If true use random displacement days in dates entities,if false use the DeIdentificationParams.days The default value is false.

Whether to keep the month intact when obfuscating date entities. If true, the month will remain unchanged during the obfuscation process. If false, the month will be modified along with the year and day. Default: false.

It specifies whether the output should maintain the same character length as the input text. the output text will remain the same if same length is available, else length might vary.

Whether to keep the year intact when obfuscating date entities. If true, the year will remain unchanged during the obfuscation process. If false, the year will be modified along with the month and day. Default: false.

The language used to select the regex file and some faker entities. 'en'(English),'de'(German), 'es'(Spanish), 'fr'(French), 'ar'(Arabic) or 'ro'(Romanian) Default:'en'

This is the mapping column that will return the Annotations chunks with the fake entities

Select the masking policy:

• 'entity_labels': Replace the values with the entity value.
• 'same_length_chars': Replace the name with the asterix with same length minus two plus brackets on both end.If the entity is less than 3 chars (like Jo, or 5), we can just use asterix without brackets.
• 'fixed_length_chars': Replace the obfuscated entity with a masking sequence composed of a fixed number of asterisk.
• 'entity_labels_without_brackets': Replace the values with the entity value without brackets.
• 'same_length_chars_without_brackets': Replace the name with the asterix with same length without brackets.
• Default: 'entity_labels'

If specified, the metadata includes the masked form of the document. Select the following masking policy if you want to return mask form in the metadata:

• 'entity_labels': Replace the values with the entity value.
• 'same_length_chars': Replace the name with the asterix with same length minus two plus brackets on both end.If the entity is less than 3 chars (like Jo, or 5), we can just use asterix without brackets.
• 'fixed_length_chars': Replace the obfuscated entity with a masking sequence composed of a fixed number of asterisk.
• 'entity_labels_without_brackets': Replace the values with the entity value without brackets.
• 'same_length_chars_without_brackets': Replace the name with the asterix with same length without brackets.
• Default: ""

Minimum year to use when converting date to year

Mode for Anonymizer ['mask' or 'obfuscate']. Default: 'mask'

• Mask mode: The entities will be replaced by their entity types.
• Obfuscate mode: The entity is replaced by an obfuscator's term.

Whether to obfuscate ages based on age groups.

When true, the age groups specified in the ageGroups parameter will be used to obfuscate ages. When false, the age ranges specified in the ageRanges parameter will be used to obfuscate ages. Default: false.

When mode=="obfuscate" whether to obfuscate dates or not. This param helps in consistency to make dateFormats more visible. When setting to true, make sure dateFormats param fits the needs. If the value is true and obfuscation is failed, then unnormalizedDateMode will be activated. When setting to 'false', then the date will be masked to <DATE>. Default: false

File with the terms to be used for Obfuscation

The source of obfuscation to obfuscate the entities. The values ar the following: 'file': Takes the entities from the obfuscatorRefFile 'faker': Takes the entities from the Faker module 'both': Takes the entities from the obfuscatorRefFile and the faker module randomly.

variant-to-canonical entity mappings to ensure consistent obfuscation.

This method allows you to define equivalence rules for entity variants that should be obfuscated the same way. For example, the names "Alex" and "Alexander" will always be mapped to the same obfuscated value if they are linked to the same canonical form.

It accepts an array of string triplets, where each triplet defines:

• variant: A non-standard, short, or alternative form of a value (e.g., "Alex")
• entityType: The type of the entity (e.g., "NAME", "STATE", "COUNTRY")
• canonical: The standardized form all variants map to (e.g., "Alexander")

variant and entityType comparisons are case-insensitive during processing.

This is especially useful in de-identification tasks to ensure consistent replacement of semantically identical values. It also allows cross-variant normalization across different occurrences of sensitive data.

variant-to-canonical entity mappings to ensure consistent obfuscation.

This method allows you to define equivalence rules for entity variants that should be obfuscated the same way. For example, the names "Alex" and "Alexander" will always be mapped to the same obfuscated value if they are linked to the same canonical form.

It accepts an array of string triplets, where each triplet defines:

• variant: A non-standard, short, or alternative form of a value (e.g., "Alex")
• entityType: The type of the entity (e.g., "NAME", "STATE", "COUNTRY")
• canonical: The standardized form all variants map to (e.g., "Alexander")

This is especially useful in de-identification tasks to ensure consistent replacement of semantically identical values. It also allows cross-variant normalization across different occurrences of sensitive data.

The obfuscation strategy to be applied when an exception occurs.

The obfuscation strategy determines how obfuscation is handled in case of an exception. Four possible values are supported:

• "mask": The original chunk is replaced with a masking pattern.
• "default": The original chunk is replaced with a default faker.
• "skip": The original chunk is not replaced with any faker.
• "exception": Throws the exception.

The default obfuscation strategy is "default".

Output annotator types: DOCUMENT

Whether to return all sentences joined into a single document

Format of the reference file for Obfuscation the default value for that is "csv"

Separator character for the csv reference file for Obfuscation de default value is "#"

If the value is true, prioritize the regex entities; if the value is false, prioritize the ner. The default value is false. If DeIdentification.combineRegexPatterns is true, this value will be invalid.

With this property, you can select particular dateFormats. This property is especially used when obfuscating dates. You can decide whether the first part of 11/11/2023 is a day or the second part is a day when obfuscating dates.

• The values are following:
• 'eu' for European Union
• 'us' for USA

With this property, you can select if you want to return mapping column.

Similarity threshold [0.0-1.0] to consider two appearances of an entity as the same (default: 0.9) For date entities this method doesn't apply.

List of formatted entities to generate the same length outputs as original ones during obfuscation. The supported and default formatted entities are: "phone", "fax", "contact," "id", "idnum", "bioid", "medicalrecord", "zip", "vin", "ssn", "dln", "plate", "license", "IRS", "CFN", "account".

It is the seed to select the entities on obfuscate mode. With the seed, you can reply to an execution several times with the same output.

A map of entity names to their obfuscation modes. This is used to selectively apply different obfuscation methods to specific entities. The keys are entity names and the values are the obfuscation sources. If an entity is not specified in this map, the obfuscateRefSource param is used to determine the obfuscation source.

The dictionary of modes to enable multi-mode deidentification.

• 'obfuscate': Replace the values with random values.
• 'mask_same_length_chars': Replace the name with the asterix with same length minus two plus brackets on both end.
• 'mask_entity_labels': Replace the values with the entity value.
• 'mask_fixed_length_chars': Replace the name with the asterix with fixed length. You can also invoke "setFixedMaskLength()"
• 'mask_entity_labels_without_brackets': Replace the values with the entity value without brackets.
• 'mask_same_length_chars_without_brackets': Replace the name with the asterix with same length without brackets.
• 'skip': Skip the entities (intact)

The entities which have not been given in dictionary will deidentify according to setMode()

Sets additionalDateFormats param

Sets the age groups to obfuscate ages. For this parameter to be active, the obfuscateByAgeGroups parameter must be true. If the given ageGroups do not fully contain the ages, the ages continue to be obfuscated according to the ageRanges. The map should contain the age group name as the key and an array of two integers as the value. The first integer is the lower bound of the age group, and the second integer is the upper bound of the age group. Default age groups are as follows in the English language:

Map(
"baby" -> Array(0, 1),
"toddler" -> Array(1, 3),
"child" -> Array(3, 12),
"teenager" -> Array(12, 20),
"adult" -> Array(20, 65),
"senior" -> Array(65, 200)
)

List of integers specifying limits of the age groups to preserve during obfuscation

Sets whether to obfuscate ages based on HIPAA (Health Insurance Portability and Accountability Act) Privacy Rule.

The HIPAA Privacy Rule mandates that ages from patients older than 90 years must be obfuscated, while age for patients 90 years or younger can remain unchanged.

List of entities that will be ignored to in the regex file. The rest will be processed. The default values are "IBAN","ZIP","NPI","DLN","PASSPORT","C_CARD","DEA","SSN", "IP", "DEA".

Sets the list of entities coming from NER or regex rules that will be ignored for masking or obfuscation. The rest entities will be processed. Defaults to an empty array.

Performs entity chunk matching across rows or within groups in a DataFrame. Useful in de-identification pipelines where certain entity labels like "NAME" or "DATE" may be missing in some rows and need to be filled from other rows in the same group.

Notes:

• When applying the method across multiple rows, the usage of groupByCol parameter is required.

If the value is true both loaded regex file and default regex file are used together; if the value is false, either loaded regex file or default regex file is used. The default value is false If the value is true, it uses the default regex file regardless of the value of the regexOverride.

Sets the value of consistentAcrossNameParts.

Whether to replace very similar entities in a document with the same randomized term (default: true) The similarity is based on the Levenshtein Distance between the words.

Sets whether to obfuscate country entities or not. If true, country entities will be obfuscated using the Faker module. If false, country entities will be skipped during obfuscation. Default: false

Sets the value of dateEntities. Default: Array("DATE", "DOB", "DOD", "EFFDATE", "FISCAL_YEAR")

Format of dates to displace

Tag representing what are the NER entity (default: DATE)

true if dates must be converted to years, false otherwise

Number of days to obfuscate the dates by displacement. If not provided a random integer between 1 and 60 will be used

If true, exceptions are handled. If exception causing data is passed to the model, a error annotation is emitted which has the exception message. Processing continues with the next one. This comes with a performance penalty.

Sets whether to enable default obfuscation equivalents for common entities. This parameter allows the system to automatically include a set of predefined common English name equivalents. Default: false

Dictionary path where is the json that contains the entity casing modes. 'lowercase': Converts all characters to lower case using the rules of the default locale. 'uppercase': Converts all characters to upper case using the rules of the default locale. 'capitalize': Converts the first character to upper case and converts others to lower case. 'titlecase': Converts the first character in every token to upper case and converts others to lower case.

Sets fakerLengthOffset param

Sets the value of fixedMaskLength. This is the length of the masking sequence that will be used when the 'fixed_length_chars' masking policy is selected.

Whether to use gender-aware names or not during obfuscation. This param effects only names. If value is true, it might decrease performance. Default: False

Sets the value of geoConsistency. When set to true, it enables consistent obfuscation across geographical entities such as state, city, street, zip, and phone.

Sets groupByCol param to group the dataset. This parameter is used in conjunction with consistentObfuscation to ensure consistent obfuscation within each group.

Select if you want to use regex file loaded in the model. If true the default regex file will be not used The default value is false.

Use a random displacement days in dates entities,that random number is based on the DeIdentificationParams.seed If true use random displacement days in dates entities, if false use the DeIdentificationParams.days The default value is false.

Sets whether to keep the month intact when obfuscating date entities. If true, the month will remain unchanged during the obfuscation process. If false, the month will be modified along with the year and day. Default: false.

Sets keepTextSizeForObfuscation param

Sets whether to keep the year intact when obfuscating date entities. If true, the year will remain unchanged during the obfuscation process. If false, the year will be modified along with the month and day. Default: false.

The language used to select the regex file and some faker entities. 'en'(English),'de'(German), 'es'(Spanish), 'fr'(French), 'ar'(Arabic) or 'ro'(Romanian). Default:'en'

This is the mapping column that will return the Annotations chunks with the fake entities

Select the masking policy:

• 'entity_labels': Replace the values with the entity value.
• 'same_length_chars': Replace the name with the asterix with same length minus two plus brackets on both end.If the entity is less than 3 chars (like Jo, or 5), we can just use asterix without brackets.
• 'fixed_length_chars': Replace the obfuscated entity with a masking sequence composed of a fixed number of asterisk.
• 'entity_labels_without_brackets': Replace the values with the entity value without brackets.
• 'same_length_chars_without_brackets': Replace the name with the asterix with same length without brackets.
• Default: 'entity_labels'

If specified, the metadata includes the masked form of the document. Select the following masking policy if you want to return mask form in the metadata:

• 'entity_labels': Replace the values with the entity value.
• 'same_length_chars': Replace the name with the asterix with same length minus two plus brackets on both end.If the entity is less than 3 chars (like Jo, or 5), we can just use asterix without brackets.
• 'fixed_length_chars': Replace the obfuscated entity with a masking sequence composed of a fixed number of asterisk.
• 'entity_labels_without_brackets': Replace the values with the entity value without brackets.
• 'same_length_chars_without_brackets': Replace the name with the asterix with same length without brackets.
• Default: ""

Minimum year to use when converting date to year

Mode for Anonymizer ['mask'|'obfuscate']. Default: 'mask'

• Mask mode: The entities will be replaced by their entity types.
• Obfuscate mode: The entity is replaced by an obfuscator's term.

Sets whether to obfuscate ages based on age groups.

When true, the age groups specified in the ageGroups parameter will be used to obfuscate ages. When false, the age ranges specified in the ageRanges parameter will be used to obfuscate ages. Default: false.

When mode=="obfuscate" whether to obfuscate dates or not. This param helps in consistency to make dateFormats more visible. When setting to true, make sure dateFormats param fits the needs. If the value is true and obfuscation is failed, then unnormalizedDateMode will be activated. When setting to 'false' then the date will be masked to <DATE> . Default: false

File with the terms to be used for Obfuscation

The source of obfuscation to obfuscate the entities. The values are the following: 'file': Takes the fakes from the obfuscatorRefFile 'faker': Takes the fakes from the Faker module 'both': Takes the fakes from the obfuscatorRefFile and the faker module randomly.

Sets variant-to-canonical entity mappings to ensure consistent obfuscation.

This method allows you to define equivalence rules for entity variants that should be obfuscated the same way. For example, the names "Alex" and "Alexander" will always be mapped to the same obfuscated value if they are linked to the same canonical form.

It accepts an array of string triplets, where each triplet defines:

• variant: A non-standard, short, or alternative form of a value (e.g., "Alex")
• entityType: The type of the entity (e.g., "NAME", "STATE", "COUNTRY")
• canonical: The standardized form all variants map to (e.g., "Alexander")

variant and entityType comparisons are case-insensitive during processing.

This is especially useful in de-identification tasks to ensure consistent replacement of semantically identical values. It also allows cross-variant normalization across different occurrences of sensitive data.

Example

val equivalents = Array(
  Array("Alex", "NAME", "Alexander"),
  Array("Rob", "NAME", "Robert"),
  Array("CA", "STATE", "California"),
  Array("Calif.", "STATE", "California")
)

myDeidTransformer.setObfuscationEquivalents(equivalents)

Sets obfuscationEquivalents param.

Sets the static obfuscation pairs resource using a path and readAs format. The resource should contain three columns: variant, entityType, and canonical. The delimiter for the columns can be specified in the options.

Sets the obfuscation equivalents resource. The resource should contain three columns: variant, entityType, and canonical. The delimiter for the columns can be specified in the options.

Sets the obfuscation strategy to be applied when an exception occurs.

The obfuscation strategy determines how obfuscation is handled in case of an exception. Four possible values are supported:

• "mask": The original chunk is replaced with a masking pattern.
• "default": The original chunk is replaced with a default faker.
• "skip": The original chunk is not replaced with any faker.
• "exception": Throws the exception.

The default obfuscation strategy is "default".

Whether to return all sentences joined into a single document

File with the terms to be used for Obfuscation

Separator character for the csv reference file for Obfuscation de default value is "#"

If the value is true, prioritize the regex entities; if the value is false, prioritize the ner. The default value is false. If DeIdentification.combineRegexPatterns is true, this value will be invalid.

dictionary with regular expression patterns that match some protected entity.When the field is not set then a default regex file will be used.

dictionary with regular expression patterns that match some protected entity.When the field is not set then a default regex file will be used.

dictionary with regular expression patterns given as JSON that match some protected entity.When the field is not set then a default regex file will be used.

With this property, you can select particular dateFormats. This property is especially used when obfuscating dates. You can decide whether the first part of 11/11/2023 is a day or the second part is a day when obfuscating dates. The values are following:

• 'eu' for European Union
• 'us' for USA

With this property, you can select if you want to return mapping column.

Similarity threshold [0.0-1.0] to consider two appearances of an entity as the same (default: 0.9) For date entities this method doesn't apply.

List of formatted entities to generate the same length outputs as original ones during obfuscation. The supported and default formatted entities are: PHONE, FAX, CONTACT, ID, IDNUM, BIOID, MEDICALRECORD, ZIP, VIN, SSN, DLN, LICENSE, PLATE, IRS, CFN, ACCOUNT.

It is the seed to select the entities on obfuscate mode. With the seed, you can reply to an execution several times with the same output.

Sets the value of selectiveObfuscateRefSource. This is used to selectively apply different obfuscation methods to specific entities. The keys are entity names and the values are the obfuscation sources. If an entity is not specified in this map, the obfuscateRefSource param is used to determine the obfuscation method. The values can be: - 'file': Takes the fakes from the file. - 'faker': Takes the fakes from the embedded faker module. - 'both': Takes the fakes from the file and the faker module.

Sets the value of selectiveObfuscationModes. The dictionary of modes to enable multi-mode deidentification.

• 'obfuscate': Replace the values with random values.
• 'mask_same_length_chars': Replace the name with the asterix with same length minus two plus brackets on both end.
• 'mask_entity_labels': Replace the values with the entity value.
• 'mask_fixed_length_chars': Replace the name with the asterix with fixed length. You should also invoke "setFixedMaskLength()"
• 'mask_entity_labels_without_brackets': Replace the values with the entity value without brackets.
• 'mask_same_length_chars_without_brackets': Replace the name with the asterix with same length without brackets.
• 'skip': Skip the entities (intact)

The entities which have not been given in dictionary will deidentify according to setMode()

Example:

deidAnnotator
.setMode("mask")
.setSelectiveObfuscationModes(Map(
    "OBFUSCATE" -> Array("PHONE", "email"),
    "mask_entity_labels" -> Array("NAME", "CITY"),
    "skip" -> Array("id", "idnum"),
    "mask_same_length_chars" -> Array("fax"),
    "mask_fixed_length_chars" -> Array("zip")
))
.setFixedMaskLength(4)

Sets the static obfuscation pairs. Each pair should contain three elements: original, entity type, and fake. The pairs must have exactly 3 elements: [original, entityType, fake].

Sets the static obfuscation pairs resource using a path and readAs format. The resource should contain three columns: original, entity, and fake. The delimiter for the columns can be specified in the options.

Sets the static obfuscation pairs resource. The resource should contain three columns: original, entity, and fake. The delimiter for the columns can be specified in the options. The options must include a 'delimiter' key.

The mode to use if the date is not formatted. Options: [mask, obfuscate, skip] Default: obfuscate

Sets the value of useShiftDays. Whether to use the random shift day when the document has this in its metadata. DocumentHashCoder can create 'dateshift' based on the document. Default: false

A resource containing static obfuscation pairs. Each pair should contain three elements: original, entity type, and fake.

Resource containing static obfuscation pairs. The resource should contain three columns: original, entity, and fake. The delimiter for the columns can be specified in the options.

Returns the DeIdentificationModel Transformer, that can be used to transform input datasets

The dataset provided to the fit method should have one chunk per row and contain the following columns: Document, Tokens, Chunks

This method is called inside the AnnotatorApproach's fit method

The mode to use if the date is not formatted. Options: [mask, obfuscate, skip] Default: obfuscate

Use shift days : Whether to use the random shift day when the document has this in its metadata. Default: False

Whether to use the random shift day when the document has this in its metadata. DocumentHashCoder can create 'dateshift' based on the document. Default: false