# Package opennlp.tools.sentdetect

Package related to identifying sentece boundries.

- Interface Summary
  Interface | Description
  --- | ---
  EndOfSentenceScanner | Scans Strings, StringBuffers, and char[] arrays for the offsets of sentence ending characters.
  SDContextGenerator | Interface for `SentenceDetectorME` context generators.
  SentenceDetector | The interface for sentence detectors, which find the sentence boundaries in a text.
  SentenceDetectorEvaluationMonitor |

- Class Summary
  Class | Description
  --- | ---
  DefaultEndOfSentenceScanner | Default implementation of the `EndOfSentenceScanner`.
  DefaultSDContextGenerator | Generate event contexts for maxent decisions for sentence detection.
  EmptyLinePreprocessorStream | Stream to to clean up empty lines for empty line separated document streams. - Skips empty line at training data start - Transforms multiple empty lines in a row into one - Replaces white space lines with empty lines - TODO: Terminates last document with empty line if it is missing This stream should be used by the components that mark empty lines to mark document boundaries.
  NewlineSentenceDetector | The Newline Sentence Detector assumes that sentences are line delimited and recognizes one sentence per non-empty line.
  SDCrossValidator | A cross validator for the sentence detector.
  SDEventStream |
  SentenceDetectorEvaluator | The `SentenceDetectorEvaluator` measures the performance of the given `SentenceDetector` with the provided reference `SentenceSample`s.
  SentenceDetectorFactory | The factory that provides SentenceDetecor default implementations and resources
  SentenceDetectorME | A sentence detector for splitting up raw text into sentences.
  SentenceModel | The `SentenceModel` is the model used by a learnable `SentenceDetector`.
  SentenceSample | A `SentenceSample` contains a document with begin indexes of the individual sentences.
  SentenceSampleStream | This class is a stream filter which reads a sentence by line samples from a `Reader` and converts them into `SentenceSample` objects.