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  • Installation
  • Quick Start Guide
  • And There’s More
  • Contributing
  • About
    • Supported By
    • License

NLP with Forte

  • Chapter 1. Handling Structured Data
    • Building and Understanding Ontology
      • A first glimpse of ontology generation
      • Before we start
      • A simple ontology config
        • Breakdown of the simple ontology
      • Major ontology types, Annotations, Links, Groups and Generics
      • Importing another ontology
      • Package Naming Convention
      • Generating Python classes from ontology.
        • Ontology Generation Steps
        • Cleaning the generated ontology
    • Handling Structured Data in DataPack
      • Related Readings
      • Retrieve data
        • Annotation
        • AudioAnnotation
      • Build Coverage Index
  • Chapter 2. Building NLP Pipeline
    • Pipeline
      • Basics
      • An working example
      • Life Cycle
      • Pseudocode with PipelineComponent
    • Pipeline Component
      • Basics
        • Related Readings
      • Reader
        • Related Readings
        • Functions
        • Examples
      • Processor
        • Related Readings
        • Functions
      • Selector
        • Related Readings
    • Machine Translation Inference Pipeline
      • Packages
      • Background
      • Inference Workflow
        • Pipeline
        • Reader
        • Processor
        • Examples
    • Zero-Shot Text Classification
      • Introduction
      • Dataset
        • Data Visualization
      • Prediction
      • Evaluation
        • Aggregate
        • Accuracy
      • Experiment
      • HomeWork
  • Chapter 3. Information Extraction
    • Named Entity Recognition
    • Relation Extraction
    • Medical Notes Analysis System
  • Chapter 4. Information Retrieval
    • Indexing
    • Ranking
  • Chapter 5. Machine Translation
    • Machine Translation System
    • Building a Machine Translation System with Forte
      • Overview
      • Start with the Reader
        • Overview
        • DataPack
      • Add a pre-built Forte processor to the pipeline
        • Overview
        • Ontology
      • Create a Machine Translation Processor
        • Overview
      • A better way to store source and target text: MultiPack
        • Overview
      • New Requirement: Handle HTML data
        • Overview
      • How to preserve HTML tags/structures
        • Selector
      • Replace our MT model with online translation API
        • Overview
      • Save the whole pipeline with save()
        • Overview
  • Chapter 6. Text Generation
    • Text Generation
  • Chapter 7. Question Answering
    • Question Answering
  • Chapter 8. Chatbot
    • Chatbot
    • Eliza Example
      • Introduction
      • Quick Start
        • Install Dependencies
        • Start an Eliza pipeline service
        • Visualize the chatbot in stave
      • Code Explained
        • Overview
        • Start a Pipeline Service
        • Call a Pipeline Service
        • Create Your Own Chatbot Service
  • Chapter 9. Tasks on Other modalities
    • Audio Processing
      • Basics
        • Audio DataPack
        • Audio Reader
      • Automatic Speech Recognition
      • Speaker Segmentation
      • Example script
    • Automatic Speech Recognition
      • Wav2Vec2
      • Speaker Segmentation
      • Speech To Text
      • Output
    • Image Processing
    • Optical character recognition
      • Introduction
      • Installation
      • Pipeline Components for OCR
        • OCR Reader
        • OCR Character Processor
        • OCR Token Processor
      • Conclusion
      • Discussion

APPENDICES

  • Appendices
    • Core Design Principles
  • Glossary
  • Examples

API

  • Common
    • Exceptions
    • Configuration
    • Configurable
    • Resources
  • Data
    • Ontology
      • base
      • core
      • Entry
      • top
    • Packs
      • BasePack
      • DataPack
      • MultiPack
      • BaseMeta
      • Meta
      • DataIndex
    • MultiPack
      • MultiPackMeta
      • MultiPack
      • MultiPackLink
      • MultiPackGroup
    • Readers
      • BaseReader
      • PackReader
      • MultiPackReader
      • CoNLL03Reader
      • ConllUDReader
      • BaseDeserializeReader
      • RawDataDeserializeReader
      • RecursiveDirectoryDeserializeReader
      • HTMLReader
      • MSMarcoPassageReader
      • MultiPackSentenceReader
      • MultiPackTerminalReader
      • OntonotesReader
      • PlainTextReader
      • ProdigyReader
      • RACEMultiChoiceQAReader
      • StringReader
      • SemEvalTask8Reader
      • OpenIEReader
      • SquadReader
      • ClassificationDatasetReader
    • Selector
      • Selector
      • DummySelector
      • SinglePackSelector
      • NameMatchSelector
      • RegexNameMatchSelector
      • FirstPackSelector
      • AllPackSelector
    • Index
      • BaseIndex
    • Store
      • BaseStore
    • Data Store
      • DataStore
    • DataPack Dataset
      • DataPackIterator
      • DataPackDataset
      • RawExample
      • FeatureCollection
    • Batchers
      • ProcessingBatcher
      • FixedSizeDataPackBatcherWithExtractor
      • FixedSizeRequestDataPackBatcher
      • FixedSizeMultiPackProcessingBatcher
      • FixedSizeDataPackBatcher
    • Caster
      • Caster
      • MultiPackBoxer
      • MultiPackUnboxer
    • Container
      • EntryContainer
    • Types
      • ReplaceOperationsType
      • DataRequest
      • MatrixLike
    • Data Utilities
      • maybe_download
      • batch_instances
      • merge_batches
      • slice_batch
      • dataset_path_iterator
    • Entry Utilities
      • create_utterance
      • get_last_utterance
  • Pipeline
    • Process Pipeline
    • Train Pipeline
    • Pipeline Component
    • Process
      • ProcessJobStatus
      • ProcessManager
  • Processors
    • Base Processors
      • BaseProcessor
      • BasePackProcessor
      • BaseBatchProcessor
      • PackingBatchProcessor
      • MultiPackBatchProcessor
      • RequestPackingProcessor
      • FixedSizeBatchProcessor
      • Predictor
    • Pack Processors
      • PackProcessor
      • MultiPackProcessor
    • Task Processors
      • ElizaProcessor
      • SubwordTokenizer
      • CoNLLNERPredictor
      • SRLPredictor
      • VocabularyProcessor
      • Alphabet
      • PeriodSentenceSplitter
      • WhiteSpaceTokenizer
      • RemoteProcessor
      • LowerCaserProcessor
      • DeleteOverlapEntry
      • AttributeMasker
      • AnnotationRemover
  • Models
    • Named Entity Recognizer
    • Semantic Role Labeling
  • Training System
    • Train Preprocessor
    • Converter
      • Feature
    • Extractor
      • BaseExtractor
      • AttributeExtractor
      • LinkExtractor
      • SubwordExtractor
      • CharExtractor
      • BioSeqTaggingExtractor
    • Predictor
    • Feature
  • Evaluation
    • Base Evaluator
    • Task Evaluators
  • Data Augmentation
    • Data Augmentation Processors
      • BaseDataAugmentProcessor
      • DataAugProcessor
      • ReplacementDataAugmentProcessor
      • BaseElasticSearchDataSelector
      • RandomDataSelector
      • QueryDataSelector
      • UDAIterator
    • Data Augmentation Ops
      • TextReplacementOp
      • SingleAnnotationAugmentOp
      • DistributionReplacementOp
      • Sampler
      • UniformSampler
      • UnigramSampler
      • MachineTranslator
      • MarianMachineTranslator
      • BackTranslationOp
      • DictionaryReplacementOp
      • Dictionary
      • WordnetDictionary
      • TypoReplacementOp
      • CharacterFlipOp
      • WordSplittingOp
      • BaseDataAugmentationOp
      • EmbeddingSimilarityReplacementOp
      • UniformTypoGenerator
      • RandomSwapDataAugmentOp
      • RandomInsertionDataAugmentOp
      • RandomDeletionDataAugmentOp
    • Data Augmentation Models
      • Reinforcement Learning
  • Vocabulary
    • Vocabulary
      • VocabFilter
      • FrequencyVocabFilter
Forte
  • »
  • Chapter 2. Building NLP Pipeline »
  • Pipeline Component
  • Edit on GitHub

Pipeline Component¶

  • Basics
    • Related Readings
  • Reader
    • Related Readings
    • Functions
    • Examples
  • Processor
    • Related Readings
    • Functions
  • Selector
    • Related Readings
  • Relevant readings:

    • Introduction to Pipeline Component in pipeline

    • API: PipelineComponent

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