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{
    "pk": 30553,
    "title": "A Principle-Based Approach To Parsing for Machine Translation",
    "subtitle": null,
    "abstract": "Many parsing strategies for machine translation systems are based entirely on context-free grammars; to try to capture all natural language phenomena, these systems require an overwhelming number of rules; thus a translation system either has limited linguistic coverage, or poor performance (due to formidable grammar size). This paper shows how a principle based \"co-routine design\" implementation improves the parsing problem for translation. The parser consists of a skeletal structure-building mechanism that operates in conjunction with a linguisticlaly based constraint module, passing control back and forth until underspecified skeltal phrase structure is converted into a fully isntantialed  parse tree. The modularity of the parsing design accomodates lingusitic genralization, reduces the grammar size, enables extendibility, and is compatible with studies of human language processing.",
    "language": "eng",
    "license": {
        "name": "",
        "short_name": "",
        "text": null,
        "url": ""
    },
    "keywords": [],
    "section": "Linguistics I",
    "is_remote": true,
    "remote_url": "https://escholarship.org/uc/item/3vr9f13r",
    "frozenauthors": [
        {
            "first_name": "Bonnie",
            "middle_name": "J.",
            "last_name": "Dorr",
            "name_suffix": "",
            "institution": "Massachusetts Institute of Technology",
            "department": ""
        }
    ],
    "date_submitted": null,
    "date_accepted": null,
    "date_published": "1987-01-01T18:00:00Z",
    "render_galley": null,
    "galleys": [
        {
            "label": "PDF",
            "type": "pdf",
            "path": "https://journalpub.escholarship.org/cognitivesciencesociety/article/30553/galley/20402/download/"
        }
    ]
}