In the current flow for "token-classification" tasks, the output returned is not comprehendable?
For example, for a given NER task (and not POS tagging), and a given input sentence, the predict method returns a list of named entities:
In the above scenario, it is difficult to map the predicted entities to the original words/tokens in the input string. For input string "What is your name", the predict method returns ["I-Misc"] as output. There is no way to directly map this output to any token/word in the input string.
Can we please modify the results to be more comprehensive?
Thanks,
Ghanshyam
Motivation
What is the use case for this feature?
It will help to map the predicted entities back to the original words
Why is this use case valuable to support for MLflow users in general?
Without adding this support, the predicted result might not be useful
Why is this use case valuable to support for your project(s) or organization?
Without adding this support, the predicted result might not be useful
Why is it currently difficult to achieve this use case?
There is no way to map the predicted entities back to the original word
Details
No response
What component(s) does this bug affect?
[ ] area/artifacts: Artifact stores and artifact logging
[ ] area/build: Build and test infrastructure for MLflow
Willingness to contribute
Yes. I can contribute this feature independently.
Proposal Summary
Hi,
In the current flow for "token-classification" tasks, the output returned is not comprehendable?
For example, for a given NER task (and not POS tagging), and a given input sentence, the predict method returns a list of named entities:
In the above scenario, it is difficult to map the predicted entities to the original words/tokens in the input string. For input string "What is your name", the predict method returns ["I-Misc"] as output. There is no way to directly map this output to any token/word in the input string.
Can we please modify the results to be more comprehensive?
Thanks, Ghanshyam
Motivation
It will help to map the predicted entities back to the original words
Without adding this support, the predicted result might not be useful
Without adding this support, the predicted result might not be useful
There is no way to map the predicted entities back to the original word
Details
No response
What component(s) does this bug affect?
area/artifacts
: Artifact stores and artifact loggingarea/build
: Build and test infrastructure for MLflowarea/docs
: MLflow documentation pagesarea/examples
: Example codearea/gateway
: AI Gateway service, Gateway client APIs, third-party Gateway integrationsarea/model-registry
: Model Registry service, APIs, and the fluent client calls for Model Registryarea/models
: MLmodel format, model serialization/deserialization, flavorsarea/recipes
: Recipes, Recipe APIs, Recipe configs, Recipe Templatesarea/projects
: MLproject format, project running backendsarea/scoring
: MLflow Model server, model deployment tools, Spark UDFsarea/server-infra
: MLflow Tracking server backendarea/tracking
: Tracking Service, tracking client APIs, autologgingWhat interface(s) does this bug affect?
area/uiux
: Front-end, user experience, plotting, JavaScript, JavaScript dev serverarea/docker
: Docker use across MLflow's components, such as MLflow Projects and MLflow Modelsarea/sqlalchemy
: Use of SQLAlchemy in the Tracking Service or Model Registryarea/windows
: Windows supportWhat language(s) does this bug affect?
language/r
: R APIs and clientslanguage/java
: Java APIs and clientslanguage/new
: Proposals for new client languagesWhat integration(s) does this bug affect?
integrations/azure
: Azure and Azure ML integrationsintegrations/sagemaker
: SageMaker integrationsintegrations/databricks
: Databricks integrations