stanfordnlp/CoreNLP · error · IllegalArgumentException

TokensRegexNERAnnotator ERROR: Invalid priority in line in…

Error message

TokensRegexNERAnnotator ERROR: Invalid priority in line  in regexner file : ""!

What it means

When the header defines a 'priority' column, its value on each line is parsed with Double.parseDouble; a non-numeric value throws IllegalArgumentException showing the line number, mapping file, and line text. Priorities control which rule wins on overlapping matches and must be valid doubles.

Solutions

Replace the priority value on the reported line with a plain double, e.g. 1.0 or 0.
Remove the priority cell (or leave it empty and ensure the column is optional) if you don't need priorities.
Use '.' as the decimal separator, never ','.
Validate the whole file by parsing each priority column with Double.parseDouble in a pre-check script.

Example fix

// before
[ { word:/CEO/ } ]	PERSON	high
// after
[ { word:/CEO/ } ]	PERSON	1.0

Defensive patterns

Strategy: validation

Validate before calling

for (String[] row : rows) {
  String p = row[iPriority];
  if (p != null && !p.trim().isEmpty()) Double.parseDouble(p.trim()); // throws before CoreNLP does
}

Try / catch

try { annotator = new TokensRegexNERAnnotator(name, props); } catch (IllegalArgumentException e) { if (e.getMessage().contains("Invalid priority")) { fixPriorityOnLine(e.getMessage()); } else throw e; }

Prevention

Write priorities as plain doubles with '.' decimal separators
Never put descriptive labels ('high', 'N/A') in numeric columns
Lint numeric columns with Double.parseDouble in CI before shipping mapping files

When it happens

Trigger: A priority column containing text like 'high', '1st', '10%', or a localized decimal comma ('0,5') instead of a plain double such as '1.5'.

Common situations: Hand-written rule files with descriptive priorities; copy-pasted rows where a header cell slipped into the data; locale-edited numbers using commas.

Understand the failure class

Background: "Invalid ... format", "must be in format X", "does not look like a ..." — invalid argument format errors across CLI tools and libraries — this error's family across 17 libraries.

Related errors

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/5cf7f1c2ab3437ce. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/pipeline/TokensRegexNERAnnotator.java:776

          logger.warn("Number in types column for " + Arrays.toString(key) +
                  " is probably priority: " + split[iOverwrite]);
        }
        String[] tempOTs = COMMA_DELIMITERS_PATTERN.split(split[iOverwrite].trim());
        if (tempOTs.length == 0) {
          overwritableTypes = Collections.emptySet();
        } else if (tempOTs.length == 1) {
          overwritableTypes = Collections.singleton(tempOTs[0]);
        } else {
          overwritableTypes = new HashSet<>(Arrays.asList(tempOTs));
        }
      } else {
        overwritableTypes = Collections.emptySet();
      }
      if (iPriority >= 0 && split.length > iPriority) {
        try {
          priority = Double.parseDouble(split[iPriority].trim());
        } catch (NumberFormatException e) {
          throw new IllegalArgumentException("TokensRegexNERAnnotator " + annotatorName
              + " ERROR: Invalid priority in line " + lineCount
              + " in regexner file " + mappingFilename + ": \"" + line + "\"!", e);
        }
      }

      double weight = 0.0;
      if (iWeight >= 0 && split.length > iWeight) {
        try {
          weight = Double.parseDouble(split[iWeight].trim());
        } catch (NumberFormatException e) {
          throw new IllegalArgumentException("TokensRegexNERAnnotator " + annotatorName
              + " ERROR: Invalid weight in line " + lineCount
              + " in regexner file " + mappingFilename + ": \"" + line + "\"!", e);
        }
      }
      int annotateGroup = 0;
      // Get annotate group from input....
      if (iGroup>= 0 && split.length > iGroup) {

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