stanfordnlp/CoreNLP · error · IllegalArgumentException

Expected a DVModelReranker

Error message

Expected a DVModelReranker

What it means

ParseAndPrintMatrices re-ranks a parsed sentence and expects the parser query's reranker to be a DVModelReranker.Query so it can extract deep per-tree vectors. The generic RerankerQuery returned by RerankingParserQuery is type-checked with instanceof; any other reranker implementation means the tool cannot access DeepTree vectors, so it throws IllegalArgumentException.

Solutions

1. Load a parser model that was built with a DVModelReranker (pass -dvModel / train with the DV model options)
2. Check the model's options: reranker must be DVModelReranker, not TaggerReranker or another Reranker
3. If you only need parse output, use a different tool that does not require deep trees

Example fix

// before
java edu.stanford.nlp.parser.dvparser.ParseAndPrintMatrices -model parser.ser.gz
// after
java edu.stanford.nlp.parser.dvparser.ParseAndPrintMatrices -model parser.ser.gz -dvModel dvmodel.ser.gz

RerankerQuery rq = rpq.rerankerQuery();
if (!(rq instanceof DVModelReranker.Query)) {
  throw new IllegalStateException("Model was not built with DVModelReranker; re-load with -dvModel");
}

function isDVModelRerankerQuery(rq) { return rq instanceof DVModelReranker.Query; }

try {
  RerankerQuery reranker = rpq.rerankerQuery();
  if (!(reranker instanceof DVModelReranker.Query)) {
    log.warning("skipping matrix dump: reranker is " + reranker.getClass().getName());
    return;
  }
} catch (IllegalArgumentException e) {
  log.severe("DV reranker required: " + e.getMessage());
}

When it happens

Trigger: Running ParseAndPrintMatrices with a parser model whose reranker is not a DVModelReranker — e.g. a model saved with TaggerReranker (AddTaggerToParser) or no neural reranker at all, so rpq.rerankerQuery() returns a different RerankerQuery implementation.

Common situations: Users point the tool at a serialized parser trained or post-processed with a non-DV reranker, or at a parser loaded without -dvModel specified, so the cast precondition fails.

Understand the failure class

Background: Type mismatch errors: IllegalArgumentException, TypeError and type guards across 150 open-source libraries — this error's family across 150 libraries.

Related errors

• Expected a LexicalizedParser with a Reranker attached
• Expected a LexicalizedParser with a DVModel attached
• Expected a RerankingParserQuery
• addFeature was called with a features object that is…
• Unexpected node class

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/4088656805c4cd13. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/parser/dvparser/ParseAndPrintMatrices.java:120

    FileSystem.mkdirOrFail(outputFile);

    int count = 0;
    if (inputPath != null) {
      Reader input = new BufferedReader(new FileReader(inputPath));
      DocumentPreprocessor processor = new DocumentPreprocessor(input);
      for (List<HasWord> sentence : processor) {
        count++; // index from 1
        ParserQuery pq = parser.parserQuery();
        if (!(pq instanceof RerankingParserQuery)) {
          throw new IllegalArgumentException("Expected a RerankingParserQuery");
        }
        RerankingParserQuery rpq = (RerankingParserQuery) pq;
        if (!rpq.parse(sentence)) {
          throw new RuntimeException("Unparsable sentence: " + sentence);
        }
        RerankerQuery reranker = rpq.rerankerQuery();
        if (!(reranker instanceof DVModelReranker.Query)) {
          throw new IllegalArgumentException("Expected a DVModelReranker");
        }
        DeepTree deepTree = ((DVModelReranker.Query) reranker).getDeepTrees().get(0);
        IdentityHashMap<Tree, SimpleMatrix> vectors = deepTree.getVectors();

        for (Map.Entry<Tree, SimpleMatrix> entry : vectors.entrySet()) {
          log.info(entry.getKey() + "   " +  entry.getValue());
        }

        FileWriter fout = new FileWriter(outputPath + File.separator + "sentence" + count + ".txt");
        BufferedWriter bout = new BufferedWriter(fout);

        bout.write(SentenceUtils.listToString(sentence));
        bout.newLine();
        bout.write(deepTree.getTree().toString());
        bout.newLine();

        for (HasWord word : sentence) {
          outputMatrix(bout, model.getWordVector(word.word()));

View on GitHub (pinned to 1b7edd19c4)