Not enough information provided via command line properties…

Error message

Not enough information provided via command line properties or properties file.  If you want to save a model, please specify -serializeTo.  Use -help for other options.

What it means

StatTokSentTrainer.main validates that the invocation is usable: it needs something to do with the model (testFile, serializeTo, or cross-validation with >=2 folds) AND a source of the model (a training IOB file or a loadClassifier). If either side of the conjunction fails, it logs this error and returns. It prevents running an expensive pipeline that would produce or consume nothing.

Solutions

Add -serializeTo <path> if you intend to train and save a model.
Add -loadClassifier <path> if you intend to evaluate or re-serialize an existing model.
Provide -trainFileIOB <path> so there is training data.
If cross-validating, set -crossValidationFolds to >= 2 and ensure serializeTo/testFile or loadClassifier conditions are satisfied.

Example fix

// before: trains but nowhere to put the model
java -cp ... StatTokSentTrainer -trainFileIOB train.iob
// after
java -cp ... StatTokSentTrainer -trainFileIOB train.iob -serializeTo stattok.model

Defensive patterns

Strategy: validation

Validate before calling

boolean use = testFile != null || serializeTo != null || folds >= 2;
boolean source = trainFileIOB != null || loadClassifier != null;
if (!(use && source)) {
    throw new IllegalArgumentException("Need (testFile|serializeTo|folds>=2) AND (trainFileIOB|loadClassifier)");
}

Prevention

Decide train-vs-evaluate mode first, then supply exactly the matching flags.
Never omit -serializeTo for training runs you intend to keep.
Use -crossValidationFolds 5 rather than relying on defaults.

When it happens

Trigger: Running the trainer with, e.g., -trainFileIOB but no -serializeTo/-testFile, or with -serializeTo but no -trainFileIOB and no -loadClassifier, matching the guard `(testFile==null && serializeTo==null && folds<2) || (trainFileIOB==null && loadClassifier==null)`.

Common situations: Wanting to train-and-save but forgetting -serializeTo; trying to evaluate an existing model but forgetting -loadClassifier; setting crossValidationFolds to 1 or leaving it unset while also omitting serializeTo/testFile.

Understand the failure class

Background: "X is required", "must be set", "cannot be empty": the missing-required-config error family, from Vertex AI project/location to WeChat keys — this error's family across 18 libraries.

Related errors

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/cddb37e3780ee0cb. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/process/stattok/StatTokSentTrainer.java:496

    }

    logger.info("Creating classifier...");

    // Build the ColumnDataClassifier and train it on the temporary training file (or test it).
    ColumnDataClassifier cdc = new ColumnDataClassifier(classifierProps);

    String testFile 			= properties.getProperty("testFile", null);
    String serializeTo 			= properties.getProperty("serializeTo", null);
    String crossValidationFoldsStr 	= properties.getProperty("crossValidationFolds", null);
    int crossValidationFolds 		= 0;
    if (crossValidationFoldsStr != null){
      crossValidationFolds = Integer.parseInt(crossValidationFoldsStr);
    }
    String loadClassifier		= properties.getProperty("loadClassifier", null); 

    if ((testFile == null && serializeTo == null && crossValidationFolds < 2) ||
        (trainFileIOB == null && loadClassifier == null)) { 
      logger.err("Not enough information provided via command line properties or properties file.  If you want to save a model, please specify -serializeTo.  Use -help for other options.");
      return;
    }

    if (loadClassifier == null) {
      if (!cdc.trainClassifier(trainFileIOB.getPath())) {
        logger.err("Training of the CDC failed!  Unable to build StatTokSent model");
        return;
      }
      serialize(serializeTo, cdc, windowSize);
    }

    if (testFile != null) {
      cdc.testClassifier(testFile);
    }
  }
}

View on GitHub (pinned to 1b7edd19c4)