problems ValidationProblem[]List of problems that occurred while validating the file format. This list may not be exhaustive. If it's been limited, the total_problems indicate the total count. level enumLevel of the problem. 1 = Warning 2 = Fatal | message string | filename string(Optional) Filename in which the problem was encountered. | line uint32(Optional) Line of filename on which the problem was encountered. | training_phrase TrainingPhraseid string | translated_from_id stringIf this training phrase is a translation of an original training phrase, ID of the TrainingPhrase from which this training phrase was translated from. | text stringVerbatim text. In case of a fragment, copies the first user input | processed booleanWhether this fragment has been been seen in the bottom-up response creation flow | constituents string[]The divided sentences/constituents order to support multi-part. | locations PhraseLocation[]Editing a training phrase appends new locations. conversation_id stringThe conversation / context which contains the given spans | input_id stringThe normalized input / example id from the pipeline | conversation_type uint32Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType | spans SpanIndex[]The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| fragment Fragmentitems FragmentItem[]Array of inputs/placeholders found in this fragment input Inputtext string | source enumWhether the input comes from an expert or user | input_id stringThe normalized input / example id from the pipeline | created_at RFC3339The absolute timestamp when the input was uttered |
| placeholder Placeholdertag_id stringThe tag identifier representing the type of agent response that would be created at this location. See zia.ai.Playbook.Tag.id |
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| location PhraseLocationconversation_id stringThe conversation / context which contains the given spans | input_id stringThe normalized input / example id from the pipeline | conversation_type uint32Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType | spans SpanIndex[]The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| metadata TrainingPhraseMetadata | entities InputEntity[]Entities referenced in the training phrase text . If the parts field is provided on creation or update, this field is ignored and rebuilt from parts . reference EntityReferenceSync from zia.ai.playbook.EntityReference entity_id stringUnique identifier of the entity for database storage. | key stringKey by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key | text stringText used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. | value stringIf the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) | value_id stringUnique identifier of the entity value for database storage. | role stringIf entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. |
| span SpanIndexstart SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| parts InputPart[]If the training phrase contains entities, this field contains the parts of the text and the entities. The parts are concatenated to form the final text. Parts are provided to ease entity annotations. If provided at creation or update, this will override the entities field. text Text | entity EntityMatchentity EntityReferenceSync from zia.ai.playbook.EntityReference entity_id stringUnique identifier of the entity for database storage. | key stringKey by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key | text stringText used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. | value stringIf the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) | value_id stringUnique identifier of the entity value for database storage. | role stringIf entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. |
| score floatThe confidence score for this match | span Spanstart uint32The start of this entity, as the utf8 byte index | end uint32The end of this entity, as the utf8 byte index |
| extractor string(Rasa specific) Name of the pipeline component that found this entity |
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| tags TagReference[]id stringUnique identifier of the tag. | name string(Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. | protected booleanFor internal use. There is no guarantee that this will be properly filled. |
| source enumSource of the training phrase | source_info TrainingPhraseSourceInfosource_id stringID of the training phrase at its source (if applicable) | merged_ids string[]List of unique identifiers of phrase from HumanFirst or external integrations that got merged into this phrase at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. | botpress Botpress | rasa Rasa | dialogflow Dialogflowrepeat_count int32For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. |
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| created_at RFC3339Date at which first the training phrase insert was done in database (generated by server) | updated_at RFC3339Date at which last update to training phrase was done in database (generated by server) | deleted_at RFC3339If present, the date at which the training phrase was deleted from the database (generated by server) | language stringLanguage of the training phrase. If empty, 'en' is assumed. 2 letters ISO 639-1 or BCP47 locale format (ex: 'en-US'). | training_phrase_list stringIf training phrase is stored in a database, list in which this phrase is. | hash stringHash of the normalized text of the phrase, used to join embeddings data. | negative booleanIf the training phrase is associated to an intent, this indicates that it's a negative phrase | edited booleanWhether this phrase's text prop has been modified from its original version | starred boolean |
| intent IntentIntents define a component that match on some external input or condition. It's purpose is to activate it's outbound contexts whenever the condition is met id string | name string | type enum | parent_id stringThe intent's parent intent, within the same context | template_intent TemplateIntentInfotemplate_id stringTemplate from which this intent was imported | template_name string | template_intent_id stringintent id within the template | parent_names string[]List of parents, from top to bottom | template_intent_name stringOriginal intent name, in the template |
| inbound_contexts Context[]Contexts which have to be active in order for this intent to match id string | type enumThe type of intents contained by this context | position uint32The position occupied by the intent in the current context. (only populated when fetching intents) | created_at RFC3339 |
| outbound_contexts Context[]Contexts to activate if this intent is matched id string | type enumThe type of intents contained by this context | position uint32The position occupied by the intent in the current context. (only populated when fetching intents) | created_at RFC3339 |
| training_phrases TrainingPhrase[]Positive training phrases of the intent id string | translated_from_id stringIf this training phrase is a translation of an original training phrase, ID of the TrainingPhrase from which this training phrase was translated from. | text stringVerbatim text. In case of a fragment, copies the first user input | processed booleanWhether this fragment has been been seen in the bottom-up response creation flow | constituents string[]The divided sentences/constituents order to support multi-part. | locations PhraseLocation[]Editing a training phrase appends new locations. conversation_id stringThe conversation / context which contains the given spans | input_id stringThe normalized input / example id from the pipeline | conversation_type uint32Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType | spans SpanIndex[]The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| fragment Fragmentitems FragmentItem[]Array of inputs/placeholders found in this fragment input Inputtext string | source enumWhether the input comes from an expert or user | input_id stringThe normalized input / example id from the pipeline | created_at RFC3339The absolute timestamp when the input was uttered |
| placeholder Placeholdertag_id stringThe tag identifier representing the type of agent response that would be created at this location. See zia.ai.Playbook.Tag.id |
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| location PhraseLocationconversation_id stringThe conversation / context which contains the given spans | input_id stringThe normalized input / example id from the pipeline | conversation_type uint32Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType | spans SpanIndex[]The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| metadata TrainingPhraseMetadata | entities InputEntity[]Entities referenced in the training phrase text . If the parts field is provided on creation or update, this field is ignored and rebuilt from parts . reference EntityReferenceSync from zia.ai.playbook.EntityReference entity_id stringUnique identifier of the entity for database storage. | key stringKey by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key | text stringText used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. | value stringIf the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) | value_id stringUnique identifier of the entity value for database storage. | role stringIf entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. |
| span SpanIndexstart SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| parts InputPart[]If the training phrase contains entities, this field contains the parts of the text and the entities. The parts are concatenated to form the final text. Parts are provided to ease entity annotations. If provided at creation or update, this will override the entities field. text Text | entity EntityMatchentity EntityReferenceSync from zia.ai.playbook.EntityReference entity_id stringUnique identifier of the entity for database storage. | key stringKey by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key | text stringText used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. | value stringIf the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) | value_id stringUnique identifier of the entity value for database storage. | role stringIf entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. |
| score floatThe confidence score for this match | span Spanstart uint32The start of this entity, as the utf8 byte index | end uint32The end of this entity, as the utf8 byte index |
| extractor string(Rasa specific) Name of the pipeline component that found this entity |
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| tags TagReference[]id stringUnique identifier of the tag. | name string(Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. | protected booleanFor internal use. There is no guarantee that this will be properly filled. |
| source enumSource of the training phrase | source_info TrainingPhraseSourceInfosource_id stringID of the training phrase at its source (if applicable) | merged_ids string[]List of unique identifiers of phrase from HumanFirst or external integrations that got merged into this phrase at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. | botpress Botpress | rasa Rasa | dialogflow Dialogflowrepeat_count int32For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. |
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| created_at RFC3339Date at which first the training phrase insert was done in database (generated by server) | updated_at RFC3339Date at which last update to training phrase was done in database (generated by server) | deleted_at RFC3339If present, the date at which the training phrase was deleted from the database (generated by server) | language stringLanguage of the training phrase. If empty, 'en' is assumed. 2 letters ISO 639-1 or BCP47 locale format (ex: 'en-US'). | training_phrase_list stringIf training phrase is stored in a database, list in which this phrase is. | hash stringHash of the normalized text of the phrase, used to join embeddings data. | negative booleanIf the training phrase is associated to an intent, this indicates that it's a negative phrase | edited booleanWhether this phrase's text prop has been modified from its original version | starred boolean |
| negative_training_phrases TrainingPhrase[]Negative training phrases of the intent id string | translated_from_id stringIf this training phrase is a translation of an original training phrase, ID of the TrainingPhrase from which this training phrase was translated from. | text stringVerbatim text. In case of a fragment, copies the first user input | processed booleanWhether this fragment has been been seen in the bottom-up response creation flow | constituents string[]The divided sentences/constituents order to support multi-part. | locations PhraseLocation[]Editing a training phrase appends new locations. conversation_id stringThe conversation / context which contains the given spans | input_id stringThe normalized input / example id from the pipeline | conversation_type uint32Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType | spans SpanIndex[]The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| fragment Fragmentitems FragmentItem[]Array of inputs/placeholders found in this fragment input Inputtext string | source enumWhether the input comes from an expert or user | input_id stringThe normalized input / example id from the pipeline | created_at RFC3339The absolute timestamp when the input was uttered |
| placeholder Placeholdertag_id stringThe tag identifier representing the type of agent response that would be created at this location. See zia.ai.Playbook.Tag.id |
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| location PhraseLocationconversation_id stringThe conversation / context which contains the given spans | input_id stringThe normalized input / example id from the pipeline | conversation_type uint32Type of conversation the phrase was found in. Numeric value of zia.ai.model.ConversationType | spans SpanIndex[]The spans (conversation fragments) that represent this phrase. Multiple spans can be defined in the event where the relevant portions of text are separated. start SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| metadata TrainingPhraseMetadata | entities InputEntity[]Entities referenced in the training phrase text . If the parts field is provided on creation or update, this field is ignored and rebuilt from parts . reference EntityReferenceSync from zia.ai.playbook.EntityReference entity_id stringUnique identifier of the entity for database storage. | key stringKey by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key | text stringText used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. | value stringIf the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) | value_id stringUnique identifier of the entity value for database storage. | role stringIf entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. |
| span SpanIndexstart SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
| end SpanPositioninput_index uint32The index of the input the span refers to. This index is inclusive on both start and end positions. Ex: input 0 + input 1 => start=0, end=1 | character_index uint32The byte index of the input. This index is inclusive on the start position, and exclusive on the end position. Ex: hello world, span of 'hello' => start=0, end=5, span of 'world' => start=6, end=11 Caution: When using encoding in which multiple bytes may represent a single displayable character (e.g. UTF-8, emojis), the byte index should enclose all bytes that make up the displayable character. |
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| parts InputPart[]If the training phrase contains entities, this field contains the parts of the text and the entities. The parts are concatenated to form the final text. Parts are provided to ease entity annotations. If provided at creation or update, this will override the entities field. text Text | entity EntityMatchentity EntityReferenceSync from zia.ai.playbook.EntityReference entity_id stringUnique identifier of the entity for database storage. | key stringKey by which we can refer to this entity in the utterance. Ex (rasa): I'd like to visit [New York City](city) where city is the key | text stringText used to reference the entity in the utterance Ex (rasa): I'd like to visit [New York City](city) where New York City is the text. | value stringIf the reference text isn't the main entity value, this value points to the right key value to use. For example, for a city entity, if a synonym was used, this value would contain the key value it refers to in the entity. (rasa long): I went to NYC{"entity": "city", "value": "New York City"} where 'New York City' is the value (rasa short): I went to NYC(city:New York City) | value_id stringUnique identifier of the entity value for database storage. | role stringIf entity has repeated usage in the utterance, assigns role for each usage Ex (rasa): I want to fly from Berlin{"entity": "city", "role": "departure"} to San Francisco{"entity": "city", "role": "destination"}. |
| score floatThe confidence score for this match | span Spanstart uint32The start of this entity, as the utf8 byte index | end uint32The end of this entity, as the utf8 byte index |
| extractor string(Rasa specific) Name of the pipeline component that found this entity |
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| tags TagReference[]id stringUnique identifier of the tag. | name string(Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. | protected booleanFor internal use. There is no guarantee that this will be properly filled. |
| source enumSource of the training phrase | source_info TrainingPhraseSourceInfosource_id stringID of the training phrase at its source (if applicable) | merged_ids string[]List of unique identifiers of phrase from HumanFirst or external integrations that got merged into this phrase at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. | botpress Botpress | rasa Rasa | dialogflow Dialogflowrepeat_count int32For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. |
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| created_at RFC3339Date at which first the training phrase insert was done in database (generated by server) | updated_at RFC3339Date at which last update to training phrase was done in database (generated by server) | deleted_at RFC3339If present, the date at which the training phrase was deleted from the database (generated by server) | language stringLanguage of the training phrase. If empty, 'en' is assumed. 2 letters ISO 639-1 or BCP47 locale format (ex: 'en-US'). | training_phrase_list stringIf training phrase is stored in a database, list in which this phrase is. | hash stringHash of the normalized text of the phrase, used to join embeddings data. | negative booleanIf the training phrase is associated to an intent, this indicates that it's a negative phrase | edited booleanWhether this phrase's text prop has been modified from its original version | starred boolean |
| training_phrase_list_id stringIf the intent is from database, list identifier of training phrases | negative_training_phrase_list_id stringIf the intent is from database, list identifier of negative training phrases | hidden_from_agents booleanIf true, the intent will not be visible to agents from the extension (defaults to false) | tags TagReference[]id stringUnique identifier of the tag. | name string(Optional) Only used when importing data that tag IDs are not defined yet. This will not be filled when requesting tagged objects. | protected booleanFor internal use. There is no guarantee that this will be properly filled. |
| color string | hidden_from_follow_up_suggestions booleanIf true, this intent or its children won't be available within Answer's follow-up suggestions | follow_up_after_turn_count UInt32ValueWrapper message for uint32 . The JSON representation for UInt32Value is JSON number. | follow_up_allow_repeat_after_turn_count UInt32ValueWrapper message for uint32 . The JSON representation for UInt32Value is JSON number. | follow_up_implies_parent boolean | hidden_from_automate_matches booleanIf true, it will be considered by the classifier, but will never be returned as a match to a client | generic booleanGeneric intents are only used for its hierarchy, and are not expected to hold any responses | source IntentSourceInfosource_id stringID of the intent at its source. | merged_ids string[]List of unique identifiers of intents from HumanFirst or external integrations that got merged into this intent at some point and that can be reused to ease further merges. This list may not be exhaustive and could be truncated. | botpress Botpress | rasa Rasa | dialogflow Dialogflowrepeat_count int32For Dialogflow CX, this maps to the repeatCount field of training phrase that was sourced. For Dialogflow ES, this maps to the timesAddedCount field of the training phrase that was sourced, or thecount field in the usersays object that source via an ES Agent JSON Package. |
| cognigy Cognigyrules string[]see etl/cognigy/objects.go | confirmation_sentences string[] | condition string | disambiguationSentence string | child_features boolean | entry_point string | is_reject_intent boolean | is_disabled boolean | override_intent_default_replies_as_examples string |
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| out_of_scope booleanIf true, this intent will be used as a negative class when classifying if examples are in scope or not | metadata IntentMetadatametadata MetadataEntry | description stringDescription of the intent. |
| created_at RFC3339 | updated_at RFC3339 | deleted_at RFC3339 |
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