Automatic acquisition of Chinese Verb subcategorization frame View Homepage


Ontology type: schema:MonetaryGrant     


Grant Info

YEARS

2005-2008

FUNDING AMOUNT

230000 CNY

ABSTRACT

Large-scale, high-quality lexical knowledge resources is a natural language processing system is the basic guarantee for the real text. With the development of the corpus construction and deepening of machine learning based on large-scale corpus linguistic knowledge automatic acquisition has become an inevitable trend. This application is based on the construction of Chinese Verb subcategorization frame of knowledge resources for the target, automatic acquisition focuses on Chinese Verb subcategorization frame. Sub-genre framework is to describe a verb vocabulary knowledge in its most basic form, it is the premise and basis of syntactic and lexical analysis semantic knowledge description. Statistical machine learning under the guidance of Linguistics of the present application is intended to take basic research methods. Specifically, from the perspective of linguistics focuses on the automatic acquisition process noise problems and data sparseness problem by the argument structure and meaning of the verb class information as a feature added to the maximum entropy model, the process of automatic acquisition sub-genre framework unified solve these two problems. Finally, a practical utility in the syntactic analysis applications based on evaluation mechanisms Evaluation verb subcategorization frame applications. This application will build a large-scale, high-quality Chinese verb subcategorization frame technological foundation of knowledge resources. Research methods and key technologies for automatic acquisition of knowledge of other languages ​​is also a reference methodological significance. More... »

URL

http://npd.nsfc.gov.cn/projectDetail.action?pid=60503071

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2208", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/2220", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "type": "DefinedTerm"
      }
    ], 
    "amount": {
      "currency": "CNY", 
      "type": "MonetaryAmount", 
      "value": "230000"
    }, 
    "description": "Large-scale, high-quality lexical knowledge resources is a natural language processing system is the basic guarantee for the real text. With the development of the corpus construction and deepening of machine learning based on large-scale corpus linguistic knowledge automatic acquisition has become an inevitable trend. This application is based on the construction of Chinese Verb subcategorization frame of knowledge resources for the target, automatic acquisition focuses on Chinese Verb subcategorization frame. Sub-genre framework is to describe a verb vocabulary knowledge in its most basic form, it is the premise and basis of syntactic and lexical analysis semantic knowledge description. Statistical machine learning under the guidance of Linguistics of the present application is intended to take basic research methods. Specifically, from the perspective of linguistics focuses on the automatic acquisition process noise problems and data sparseness problem by the argument structure and meaning of the verb class information as a feature added to the maximum entropy model, the process of automatic acquisition sub-genre framework unified solve these two problems. Finally, a practical utility in the syntactic analysis applications based on evaluation mechanisms Evaluation verb subcategorization frame applications. This application will build a large-scale, high-quality Chinese verb subcategorization frame technological foundation of knowledge resources. Research methods and key technologies for automatic acquisition of knowledge of other languages \u200b\u200bis also a reference methodological significance.", 
    "endDate": "2008-12-30T00:00:00Z", 
    "funder": {
      "id": "https://www.grid.ac/institutes/grid.419696.5", 
      "type": "Organization"
    }, 
    "id": "sg:grant.4948290", 
    "identifier": [
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "4948290"
        ]
      }, 
      {
        "name": "nsfc_id", 
        "type": "PropertyValue", 
        "value": [
          "60503071"
        ]
      }
    ], 
    "inLanguage": [
      "zh"
    ], 
    "keywords": [
      "research methods", 
      "maximum entropy model", 
      "basic guarantee", 
      "syntactic analysis applications", 
      "problem", 
      "linguistics", 
      "target", 
      "References", 
      "verb class information", 
      "technological foundation", 
      "data", 
      "knowledge resources", 
      "development", 
      "automatic acquisition sub-genre framework", 
      "inevitable trend", 
      "application", 
      "key technologies", 
      "construction", 
      "Linguistics", 
      "natural language processing system", 
      "process", 
      "real text", 
      "automatic acquisition", 
      "Sub-genre framework", 
      "other languages \u200b\u200bis", 
      "statistical machine", 
      "basis", 
      "perspective", 
      "verb vocabulary knowledge", 
      "sparseness problem", 
      "linguistic knowledge", 
      "evaluation mechanisms Evaluation verb subcategorization frame applications", 
      "methodological significance", 
      "argument structure", 
      "practical utility", 
      "premise", 
      "knowledge", 
      "machine", 
      "present applications", 
      "corpus construction", 
      "high-quality lexical knowledge resources", 
      "features", 
      "basic form", 
      "guidance", 
      "meaning", 
      "large-scale corpus", 
      "semantic knowledge description", 
      "deepening", 
      "lexical analysis", 
      "basic research methods", 
      "Chinese Verb subcategorization frame", 
      "automatic acquisition process noise problems", 
      "high-quality Chinese verb subcategorization frame"
    ], 
    "name": "Automatic acquisition of Chinese Verb subcategorization frame", 
    "recipient": [
      {
        "id": "https://www.grid.ac/institutes/grid.11135.37", 
        "type": "Organization"
      }, 
      {
        "affiliation": {
          "id": "https://www.grid.ac/institutes/grid.11135.37", 
          "name": "Peking University", 
          "type": "Organization"
        }, 
        "familyName": "Sui", 
        "givenName": "Zhi Fang", 
        "id": "sg:person.01231603125.08", 
        "type": "Person"
      }, 
      {
        "member": "sg:person.01231603125.08", 
        "roleName": "PI", 
        "type": "Role"
      }
    ], 
    "sameAs": [
      "https://app.dimensions.ai/details/grant/grant.4948290"
    ], 
    "sdDataset": "grants", 
    "sdDatePublished": "2019-03-07T12:39", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com.uberresearch.data.processor/core_data/20181219_192338/projects/base/nsfc_projects_0.xml.gz", 
    "startDate": "2005-12-31T00:00:00Z", 
    "type": "MonetaryGrant", 
    "url": "http://npd.nsfc.gov.cn/projectDetail.action?pid=60503071"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/grant.4948290'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/grant.4948290'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/grant.4948290'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/grant.4948290'


 

This table displays all metadata directly associated to this object as RDF triples.

100 TRIPLES      19 PREDICATES      76 URIs      67 LITERALS      5 BLANK NODES

Subject Predicate Object
1 sg:grant.4948290 schema:about anzsrc-for:2208
2 anzsrc-for:2220
3 schema:amount Ncba9ba7ea3794b21ae5499ce13f10a38
4 schema:description Large-scale, high-quality lexical knowledge resources is a natural language processing system is the basic guarantee for the real text. With the development of the corpus construction and deepening of machine learning based on large-scale corpus linguistic knowledge automatic acquisition has become an inevitable trend. This application is based on the construction of Chinese Verb subcategorization frame of knowledge resources for the target, automatic acquisition focuses on Chinese Verb subcategorization frame. Sub-genre framework is to describe a verb vocabulary knowledge in its most basic form, it is the premise and basis of syntactic and lexical analysis semantic knowledge description. Statistical machine learning under the guidance of Linguistics of the present application is intended to take basic research methods. Specifically, from the perspective of linguistics focuses on the automatic acquisition process noise problems and data sparseness problem by the argument structure and meaning of the verb class information as a feature added to the maximum entropy model, the process of automatic acquisition sub-genre framework unified solve these two problems. Finally, a practical utility in the syntactic analysis applications based on evaluation mechanisms Evaluation verb subcategorization frame applications. This application will build a large-scale, high-quality Chinese verb subcategorization frame technological foundation of knowledge resources. Research methods and key technologies for automatic acquisition of knowledge of other languages ​​is also a reference methodological significance.
5 schema:endDate 2008-12-30T00:00:00Z
6 schema:funder https://www.grid.ac/institutes/grid.419696.5
7 schema:identifier Nac0083e7fc904079b23431ab4c2f5626
8 Nc9360d44bade44b0901a9175dded60a5
9 schema:inLanguage zh
10 schema:keywords Chinese Verb subcategorization frame
11 Linguistics
12 References
13 Sub-genre framework
14 application
15 argument structure
16 automatic acquisition
17 automatic acquisition process noise problems
18 automatic acquisition sub-genre framework
19 basic form
20 basic guarantee
21 basic research methods
22 basis
23 construction
24 corpus construction
25 data
26 deepening
27 development
28 evaluation mechanisms Evaluation verb subcategorization frame applications
29 features
30 guidance
31 high-quality Chinese verb subcategorization frame
32 high-quality lexical knowledge resources
33 inevitable trend
34 key technologies
35 knowledge
36 knowledge resources
37 large-scale corpus
38 lexical analysis
39 linguistic knowledge
40 linguistics
41 machine
42 maximum entropy model
43 meaning
44 methodological significance
45 natural language processing system
46 other languages ​​is
47 perspective
48 practical utility
49 premise
50 present applications
51 problem
52 process
53 real text
54 research methods
55 semantic knowledge description
56 sparseness problem
57 statistical machine
58 syntactic analysis applications
59 target
60 technological foundation
61 verb class information
62 verb vocabulary knowledge
63 schema:name Automatic acquisition of Chinese Verb subcategorization frame
64 schema:recipient N9d681319ea0245bb9e6b3d552262c966
65 sg:person.01231603125.08
66 https://www.grid.ac/institutes/grid.11135.37
67 schema:sameAs https://app.dimensions.ai/details/grant/grant.4948290
68 schema:sdDatePublished 2019-03-07T12:39
69 schema:sdLicense https://scigraph.springernature.com/explorer/license/
70 schema:sdPublisher N77bfe8f0e4ae45ee9f32ea89921b153c
71 schema:startDate 2005-12-31T00:00:00Z
72 schema:url http://npd.nsfc.gov.cn/projectDetail.action?pid=60503071
73 sgo:license sg:explorer/license/
74 sgo:sdDataset grants
75 rdf:type schema:MonetaryGrant
76 N77bfe8f0e4ae45ee9f32ea89921b153c schema:name Springer Nature - SN SciGraph project
77 rdf:type schema:Organization
78 N9d681319ea0245bb9e6b3d552262c966 schema:member sg:person.01231603125.08
79 schema:roleName PI
80 rdf:type schema:Role
81 Nac0083e7fc904079b23431ab4c2f5626 schema:name dimensions_id
82 schema:value 4948290
83 rdf:type schema:PropertyValue
84 Nc9360d44bade44b0901a9175dded60a5 schema:name nsfc_id
85 schema:value 60503071
86 rdf:type schema:PropertyValue
87 Ncba9ba7ea3794b21ae5499ce13f10a38 schema:currency CNY
88 schema:value 230000
89 rdf:type schema:MonetaryAmount
90 anzsrc-for:2208 schema:inDefinedTermSet anzsrc-for:
91 rdf:type schema:DefinedTerm
92 anzsrc-for:2220 schema:inDefinedTermSet anzsrc-for:
93 rdf:type schema:DefinedTerm
94 sg:person.01231603125.08 schema:affiliation https://www.grid.ac/institutes/grid.11135.37
95 schema:familyName Sui
96 schema:givenName Zhi Fang
97 rdf:type schema:Person
98 https://www.grid.ac/institutes/grid.11135.37 schema:name Peking University
99 rdf:type schema:Organization
100 https://www.grid.ac/institutes/grid.419696.5 schema:Organization
 




Preview window. Press ESC to close (or click here)


...