stanfordnlp/CoreNLP · error · RuntimeException

! wordVectors used to initialize Embedding doesn't contain…

Error message

! wordVectors used to initialize Embedding doesn't contain any recognized form of 

What it means

Embedding.getEmbeddingSize requires the supplied word-vector map to contain an entry for the unknown-word token. It looks for known UNK spellings (e.g. '<unk>') and, if none is present, throws this RuntimeException because the embedding's unknown-word vector cannot be resolved and its size (numElements) cannot be determined.

Solutions

1. Add an entry keyed '<unk>' (or the library's UNKNOWN_WORD) with a vector before constructing the Embedding
2. Use the string form constructor with a vectors file that includes an UNK line
3. Pre-process the map: wordVectors.put("<unk>", someVector)

Example fix

// before
Embedding e = new Embedding(vocabVectors); // no unk key
// after
vocabVectors.put("<unk>", new double[]{0.0, 0.0, 0.0});
Embedding e = new Embedding(vocabVectors);

if (!wordVectors.containsKey("<unk>") && !wordVectors.containsKey("UNK") && !wordVectors.containsKey("UUUNKKK"))
  wordVectors.put("<unk>", new double[expectedDim]);

boolean hasUnk = wordVectors.keySet().stream().anyMatch(k -> k.toLowerCase().contains("unk"));

try { Embedding e = new Embedding(wordVectors); } catch (RuntimeException e) { if (e.getMessage().contains("doesn't contain any recognized form")) { wordVectors.put("<unk>", defaultVector()); e = new Embedding(wordVectors); } else throw e; }

When it happens

Trigger: Calling new Embedding(Map<String,double[]>) or setWordVectors() with a map that has neither the library's default UNKNOWN_WORD key nor '<unk>' nor any recognized UNK form.

Common situations: Building embeddings from a custom word2vec/GloVe map that lacks an UNK entry; trimming vocab and dropping UNK; renaming UNK to something the library doesn't recognize.

Understand the failure class

Background: "missing required argument" and "the following required arguments were not provided": what required-argument errors mean and how to fix them — this error's family across 20 libraries.

Related errors

• Word vectors file has dimension too small for requested…
• Not sure if RVFDataset runs correctly in this method…
• minValue for feature
• maxValue for feature
• datum

AI-assisted analysis of stanfordnlp/CoreNLP@1b7edd19c4 (2026-09-10). Data as JSON: /api/errors/80a99f2cb88ce1b4. Report an issue: GitHub.

Appendix: source

Thrown at src/edu/stanford/nlp/neural/Embedding.java:308

    this.wordVectors = wordVectors;
    this.embeddingSize = getEmbeddingSize(wordVectors);
  }

  private static int getEmbeddingSize(Map<String, SimpleMatrix> wordVectors){
    if (!wordVectors.containsKey(UNKNOWN_WORD)){
      // find if there's any other unk string
      String unkStr = "";
      if (wordVectors.containsKey("UNK")) { unkStr = "UNK"; }
      if (wordVectors.containsKey("UUUNKKK")) { unkStr = "UUUNKKK"; }
      if (wordVectors.containsKey("UNKNOWN")) { unkStr = "UNKNOWN"; }
      if (wordVectors.containsKey("*UNKNOWN*")) { unkStr = "*UNKNOWN*"; }
      if (wordVectors.containsKey("<unk>")) { unkStr = "<unk>"; }

      // set UNKNOWN_WORD
      if ( ! unkStr.isEmpty()){
        wordVectors.put(UNKNOWN_WORD, wordVectors.get(unkStr));
      } else {
        throw new RuntimeException("! wordVectors used to initialize Embedding doesn't contain any recognized form of " + UNKNOWN_WORD);
      }
    }

    return wordVectors.get(UNKNOWN_WORD).getNumElements();
  }

}

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