{
  "id": "1706.00506",
  "version": "v1",
  "published": "2017-06-01T21:59:47.000Z",
  "updated": "2017-06-01T21:59:47.000Z",
  "title": "Morphological Embeddings for Named Entity Recognition in Morphologically Rich Languages",
  "authors": [
    "Onur Gungor",
    "Eray Yildiz",
    "Suzan Uskudarli",
    "Tunga Gungor"
  ],
  "comment": "Working draft",
  "categories": [
    "cs.CL"
  ],
  "abstract": "In this work, we present new state-of-the-art results of 93.59,% and 79.59,% for Turkish and Czech named entity recognition based on the model of (Lample et al., 2016). We contribute by proposing several schemes for representing the morphological analysis of a word in the context of named entity recognition. We show that a concatenation of this representation with the word and character embeddings improves the performance. The effect of these representation schemes on the tagging performance is also investigated.",
  "revisions": [
    {
      "version": "v1",
      "updated": "2017-06-01T21:59:47.000Z"
    }
  ],
  "analyses": {
    "keywords": [
      "morphologically rich languages",
      "morphological embeddings",
      "czech named entity recognition",
      "performance",
      "state-of-the-art results"
    ],
    "note": {
      "typesetting": "TeX",
      "pages": 0,
      "language": "en",
      "license": "arXiv",
      "status": "editable"
    }
  }
}