"semilabeled" meaning in All languages combined

{
  "etymology_templates": [
    {
      "args": {
        "1": "en",
        "2": "semi",
        "3": "labeled"
      },
      "expansion": "semi- + labeled",
      "name": "prefix"
    }
  ],
  "etymology_text": "semi- + labeled",
  "head_templates": [
    {
      "args": {
        "1": "-"
      },
      "expansion": "semilabeled (not comparable)",
      "name": "en-adj"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "adj",
  "senses": [
    {
      "categories": [
        {
          "kind": "other",
          "name": "English entries with incorrect language header",
          "parents": [
            "Entries with incorrect language header",
            "Entry maintenance"
          ],
          "source": "w"
        },
        {
          "kind": "other",
          "name": "English terms prefixed with semi-",
          "parents": [],
          "source": "w"
        }
      ],
      "examples": [
        {
          "ref": "2016 February 13, “Kernel Manifold Alignment for Domain Adaptation”, in PLOS ONE, →DOI",
          "text": "KEMA is as accurate as the state of the art, but with the advantage of handling naturally domains of different dimensionality, and not requiring semilabeled examples ( in the Table) to align the domains as JDA. The results obtained when using the deep DeCAF features are reported in Table 4 : a strong improvement in performance is observed for all methods.",
          "type": "quotation"
        }
      ],
      "glosses": [
        "Partially or incompletely labeled"
      ],
      "id": "en-semilabeled-en-adj-OWY1hgr3",
      "links": [
        [
          "labeled",
          "labeled"
        ]
      ],
      "tags": [
        "not-comparable"
      ]
    }
  ],
  "word": "semilabeled"
}

{
  "etymology_templates": [
    {
      "args": {
        "1": "en",
        "2": "semi",
        "3": "labeled"
      },
      "expansion": "semi- + labeled",
      "name": "prefix"
    }
  ],
  "etymology_text": "semi- + labeled",
  "head_templates": [
    {
      "args": {
        "1": "-"
      },
      "expansion": "semilabeled (not comparable)",
      "name": "en-adj"
    }
  ],
  "lang": "English",
  "lang_code": "en",
  "pos": "adj",
  "senses": [
    {
      "categories": [
        "English adjectives",
        "English entries with incorrect language header",
        "English lemmas",
        "English terms prefixed with semi-",
        "English terms with quotations",
        "English uncomparable adjectives"
      ],
      "examples": [
        {
          "ref": "2016 February 13, “Kernel Manifold Alignment for Domain Adaptation”, in PLOS ONE, →DOI",
          "text": "KEMA is as accurate as the state of the art, but with the advantage of handling naturally domains of different dimensionality, and not requiring semilabeled examples ( in the Table) to align the domains as JDA. The results obtained when using the deep DeCAF features are reported in Table 4 : a strong improvement in performance is observed for all methods.",
          "type": "quotation"
        }
      ],
      "glosses": [
        "Partially or incompletely labeled"
      ],
      "links": [
        [
          "labeled",
          "labeled"
        ]
      ],
      "tags": [
        "not-comparable"
      ]
    }
  ],
  "word": "semilabeled"
}