stanfordnlp/CoreNLP · error · IllegalArgumentException

Name and weight arrays must be of the same length

Error message

Name and weight arrays must be of the same length

What it means

SplitTrainingSet splits a treebank into named subsets by weights; it validates that the SPLIT_NAMES and SPLIT_WEIGHTS option arrays have equal length. When the number of split names differs from the number of weights, main throws this IllegalArgumentException at startup.

Solutions

1. Make splitNames and splitWeights contain the same number of comma-separated elements in the properties passed via -splitNames/-splitWeights.
2. Check for stray or missing commas that shift element counts.
3. Add an explicit weight for each named split (weights need not sum to 1 but must be positive in total).

Example fix

// before
-splitNames train,dev,test -splitWeights 0.8,0.2
// after
-splitNames train,dev,test -splitWeights 0.8,0.1,0.1

String[] names = props.getProperty("splitNames", "").split(",");
double[] ws = Arrays.stream(props.getProperty("splitWeights", "").split(","))
                    .mapToDouble(Double::parseDouble).toArray();
if (names.length != ws.length)
  throw new IllegalArgumentException("splitNames and splitWeights must have equal counts");

try {
  SplitTrainingSet.main(args);
} catch (IllegalArgumentException e) {
  if (e.getMessage() != null && e.getMessage().contains("same length")) {
    log.error("Config error: provide one weight per split name");
  } else throw e;
}

When it happens

Trigger: Invoking SplitTrainingSet.main (or filling its options) with properties where splitNames and splitWeights have different cardinalities — e.g. three names but two weights, or a weight string with a malformed/dropped element after comma splitting.

Common situations: Editing a properties/config file and adding a split name without adding its weight (or vice versa); trailing/extra commas producing an empty name entry; programmatically building the arrays with unequal lengths.

Understand the failure class

Background: "Must be a positive integer", "Invalid value", "Unsupported": the invalid-argument-value error family, when a library rejects the value you pass — this error's family across 35 libraries.

Related errors

• Split weights cannot be negative
• Conflicting properties. Multi-word rules file will be…
• Found an argument -baseModels with no actual models named
• Must specify a treebank to train from with -trainTreebank…
• Need to specify -model to load an already prepared…

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/763367c71e2221f3. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/trees/SplitTrainingSet.java:68

    int index = 0;
    for (Double weight : weights) {
      offset = offset - weight;
      if (offset < 0.0) {
        return index;
      }
      index = index + 1;
    }
    return weights.size() - 1;
  }

  @SuppressWarnings("unused")
  public static void main(String[] args) throws IOException {
    // Parse the arguments
    Properties props = StringUtils.argsToProperties(args);
    ArgumentParser.fillOptions(new Class[]{ArgumentParser.class, SplitTrainingSet.class}, props);

    if (SPLIT_NAMES.length != SPLIT_WEIGHTS.length) {
      throw new IllegalArgumentException("Name and weight arrays must be of the same length");
    }

    double totalWeight = 0.0;
    for (Double weight : SPLIT_WEIGHTS) {
      totalWeight += weight;
      if (weight < 0.0) {
        throw new IllegalArgumentException("Split weights cannot be negative");
      }
    }

    if (totalWeight <= 0.0) {
      throw new IllegalArgumentException("Split weights must total to a positive weight");
    }

    List<Double> splitWeights = new ArrayList<>();
    for (Double weight : SPLIT_WEIGHTS) {
      splitWeights.add(weight / totalWeight);
    }

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