Automatic generation of weather forecast texts using comprehensive probabilistic generation-space models
Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which pcru – a generation framework that combines probabilistic gene...
Uloženo v:
| Vydáno v: | Natural language engineering Ročník 14; číslo 4; s. 431 - 455 |
|---|---|
| Hlavní autor: | |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Cambridge, UK
Cambridge University Press
01.10.2008
|
| Témata: | |
| ISSN: | 1351-3249, 1469-8110 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which pcru – a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space – was used to semi-automatically create five different versions of a weather forecast generator. The generators were evaluated in terms of output quality, development time and computational efficiency against (i) human forecasters, (ii) a traditional handcrafted pipelined nlg system and (iii) a halogen-style statistical generator. The most striking result is that despite acquiring all decision-making abilities automatically, the best pcru generators produce outputs of high enough quality to be scored more highly by human judges than forecasts written by experts. |
|---|---|
| AbstractList | Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which
p
cru
– a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space – was used to semi-automatically create five different versions of a weather forecast generator. The generators were evaluated in terms of output quality, development time and computational efficiency against (i) human forecasters, (ii) a traditional handcrafted pipelined
nlg
system and (iii) a
halogen
-style statistical generator. The most striking result is that despite acquiring all decision-making abilities automatically, the best
p
cru
generators produce outputs of high enough quality to be scored more highly by human judges than forecasts written by experts. Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which pCRU - a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space was used to semi-automatically create five different versions of a weather forecast generator. The generators were evaluated in terms of output quality, development time and computational efficiency against (i) human forecasters, (ii) a traditional handcrafted pipelined NLG system and (iii) a HALOGEN-style statistical generator. The most striking result is that despite acquiring all decision-making abilities automatically, the best pCRU generators produce outputs of high enough quality to be scored more highly by human judges than forecasts written by experts. Adapted from the source document Abstract Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which pcru - a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space - was used to semi-automatically create five different versions of a weather forecast generator. The generators were evaluated in terms of output quality, development time and computational efficiency against (i) human forecasters, (ii) a traditional handcrafted pipelined nlg system and (iii) a halogen-style statistical generator. The most striking result is that despite acquiring all decision-making abilities automatically, the best pcru generators produce outputs of high enough quality to be scored more highly by human judges than forecasts written by experts. [PUBLICATION ABSTRACT] Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional strictly modular and sequential models. This paper reports experiments in which pcru – a generation framework that combines probabilistic generation methodology with a comprehensive model of the generation space – was used to semi-automatically create five different versions of a weather forecast generator. The generators were evaluated in terms of output quality, development time and computational efficiency against (i) human forecasters, (ii) a traditional handcrafted pipelined nlg system and (iii) a halogen-style statistical generator. The most striking result is that despite acquiring all decision-making abilities automatically, the best pcru generators produce outputs of high enough quality to be scored more highly by human judges than forecasts written by experts. |
| Author | BELZ, ANJA |
| Author_xml | – sequence: 1 givenname: ANJA surname: BELZ fullname: BELZ, ANJA organization: Natural Language Technology Group, School of Computing, Mathematical and Information Sciences, University of Brighton, Lewes Road, Brighton BN2 4GJ, UK |
| BookMark | eNp9kE9P3DAQxa2KSgXaD8DN4sAtxY4dOzki_mwrkAABZ8txxruGJF5sh26_fQ2LigDBaUaa35t587bQxuhHQGiHkp-UULl_RVlFWckbIgnhQvAvaJNy0RQ1pWQj93lcPM6_oa0Yb0mGqOSbaHEwJT_o5Ayewwghd37E3uI_oNMCArY-gNEx4QSrFPEU3TjHxg_LAAsYo3sAvAy-1a3rXXy9pohLbQAPvoM-fkdfre4j_Hiu2-jm5Pj68Fdxdj77fXhwVhjGGS9sU2tCQRLDS9t2pmx50xhgkugGoCPCdHXDK2o5o1SLSpQaSM1aaTkI3Vi2jfbWe7Or-wliUoOLBvpej-CnqOpK1KKsqwzuvgFv_RTG7E2VNAcoy7rMkFxDJvgYA1hlXHp6LgXtekWJeoxfvYs_K-kb5TK4QYe_n2qKtSYnCav_Ah3ulJBMVkrMLpWcsYsjfnqtZObZ8w09tMF1c3j54eMr_wDzxKig |
| CODEN | NLENFE |
| CitedBy_id | crossref_primary_10_1080_02564602_2018_1516522 crossref_primary_10_3390_info12090355 crossref_primary_10_1136_amiajnl_2011_000193 crossref_primary_10_1186_s40537_023_00836_y crossref_primary_10_1016_j_csl_2019_06_008 crossref_primary_10_1016_j_knosys_2020_106610 crossref_primary_10_1007_s41666_018_0036_7 crossref_primary_10_1016_j_ins_2020_03_080 crossref_primary_10_1162_tacl_a_00038 crossref_primary_10_1109_TVCG_2020_3030403 crossref_primary_10_1007_s10462_011_9216_z crossref_primary_10_1002_widm_1154 crossref_primary_10_1145_3660639 crossref_primary_10_1017_S1351324910000069 crossref_primary_10_1007_s11257_010_9076_2 crossref_primary_10_3390_math12223596 crossref_primary_10_1016_j_trit_2016_12_004 crossref_primary_10_1016_j_artmed_2012_09_002 crossref_primary_10_1016_j_csl_2017_04_009 crossref_primary_10_1109_TVCG_2015_2396062 crossref_primary_10_1017_S1351324923000207 crossref_primary_10_1007_s40747_024_01675_x crossref_primary_10_1007_s13173_012_0095_1 crossref_primary_10_1016_j_datak_2013_08_005 crossref_primary_10_1109_ACCESS_2019_2937505 crossref_primary_10_1016_j_fss_2015_06_019 crossref_primary_10_1145_1966407_1966410 crossref_primary_10_1016_j_eswa_2018_11_036 crossref_primary_10_1109_TKDE_2023_3304385 crossref_primary_10_1016_j_csl_2022_101388 crossref_primary_10_1016_j_neucom_2019_11_079 crossref_primary_10_1111_j_1756_8765_2012_01187_x crossref_primary_10_1109_ACCESS_2020_2979115 |
| Cites_doi | 10.1007/11424574_11 10.1017/CBO9780511605611.007 10.3115/1117840.1117852 10.3115/1641417.1641436 10.3115/992730.992739 10.1007/s11168-006-6327-9 10.1017/CBO9780511519857 10.3115/977180.977184 10.1109/64.294135 10.1075/idj.9.2-3.05bou 10.3115/1073336.1073337 10.3115/1289189.1289273 10.3115/100964.100979 10.3115/1219840.1219848 10.3115/974358.974361 10.21437/ICSLP.2002-303 10.1017/S1351324997001502 10.3115/974557.974596 |
| ContentType | Journal Article |
| Copyright | Copyright © Cambridge University Press 2007 |
| Copyright_xml | – notice: Copyright © Cambridge University Press 2007 |
| DBID | BSCLL AAYXX CITATION 3V. 7T9 7XB 88G 8AL 8FE 8FG 8FI 8FJ 8FK ABJCF ABUWG AEUYN AFKRA ALSLI ARAPS AZQEC BENPR BGLVJ CCPQU CPGLG CRLPW DWQXO FYUFA GHDGH GNUQQ HCIFZ JQ2 K7- L6V M0N M2M M7S P5Z P62 PHGZM PHGZT PKEHL PQEST PQGLB PQQKQ PQUKI PRINS PRQQA PSYQQ PTHSS Q9U |
| DOI | 10.1017/S1351324907004664 |
| DatabaseName | Istex CrossRef ProQuest Central (Corporate) Linguistics and Language Behavior Abstracts (LLBA) ProQuest Central (purchase pre-March 2016) Psychology Database (Alumni) Computing Database (Alumni Edition) ProQuest SciTech Collection ProQuest Technology Collection ProQuest Hospital Collection Hospital Premium Collection (Alumni Edition) ProQuest Central (Alumni) (purchase pre-March 2016) Materials Science & Engineering Collection ProQuest Central (Alumni) ProQuest One Sustainability ProQuest Central UK/Ireland Social Science Premium Collection Advanced Technologies & Computer Science Collection ProQuest Central Essentials ProQuest Central Technology Collection ProQuest One Linguistics Collection Linguistics Database ProQuest Central Health Research Premium Collection Health Research Premium Collection (Alumni) ProQuest Central Student SciTech Premium Collection ProQuest Computer Science Collection Computer Science Database ProQuest Engineering Collection Computing Database Psychology Database Engineering Database Advanced Technologies & Aerospace Database ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Premium ProQuest One Academic ProQuest One Academic Middle East (New) ProQuest One Academic Eastern Edition (DO NOT USE) ProQuest One Applied & Life Sciences ProQuest One Academic (retired) ProQuest One Academic UKI Edition ProQuest Central China ProQuest One Social Sciences ProQuest One Psychology Engineering collection ProQuest Central Basic |
| DatabaseTitle | CrossRef ProQuest One Psychology Computer Science Database ProQuest Central Student Technology Collection ProQuest One Academic Middle East (New) ProQuest Advanced Technologies & Aerospace Collection ProQuest Central Essentials ProQuest Computer Science Collection ProQuest Central (Alumni Edition) SciTech Premium Collection ProQuest One Community College ProQuest Central China ProQuest Central ProQuest One Applied & Life Sciences Linguistics Collection ProQuest One Sustainability ProQuest Engineering Collection Health Research Premium Collection ProQuest Central Korea ProQuest Central (New) Engineering Collection Advanced Technologies & Aerospace Collection Social Science Premium Collection ProQuest Computing Engineering Database ProQuest One Social Sciences ProQuest Central Basic ProQuest Computing (Alumni Edition) ProQuest One Academic Eastern Edition Linguistics and Language Behavior Abstracts (LLBA) ProQuest Hospital Collection ProQuest Technology Collection Health Research Premium Collection (Alumni) ProQuest Psychology Journals (Alumni) ProQuest SciTech Collection ProQuest Hospital Collection (Alumni) Advanced Technologies & Aerospace Database ProQuest Psychology Journals ProQuest One Academic UKI Edition Linguistics Database Materials Science & Engineering Collection ProQuest One Academic ProQuest Central (Alumni) ProQuest One Academic (New) |
| DatabaseTitleList | CrossRef Linguistics and Language Behavior Abstracts (LLBA) ProQuest One Psychology |
| Database_xml | – sequence: 1 dbid: BENPR name: ProQuest Central url: https://www.proquest.com/central sourceTypes: Aggregation Database |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Computer Science |
| DocumentTitleAlternate | A. Belz Comprehensive probabilistic generation of weather forecast texts |
| EISSN | 1469-8110 |
| EndPage | 455 |
| ExternalDocumentID | 1606667731 10_1017_S1351324907004664 ark_67375_6GQ_7G3PD4KT_7 |
| GroupedDBID | -1D -1F -2P -2V -E. -~6 -~N .DC .FH 09C 09D 0E1 0R~ 123 29M 4.4 5VS 6~7 6~8 74X 74Y 7~V 8FE 8FG 8FI 8FJ 8I0 8R4 8R5 9M5 AAAZR AABES AABWE AACJB AACJH AAFUK AAGFV AAKNA AAKTX AALKF AANRG AAPYI AARAB AASVR AATMM AAUIS AAUKB AAYOK ABBXD ABBZL ABCFY ABHFL ABITZ ABIVO ABJCF ABJNI ABJWI ABKKG ABLJU ABMWE ABQTM ABQWD ABROB ABTCQ ABTND ABUWG ABVFV ABVKB ABVZP ABXAU ABXHF ABZCX ABZUI ACABY ACAJB ACBMC ACDLN ACEJA ACETC ACGFS ACHQT ACIMK ACIWK ACOZI ACQPF ACRPL ACUIJ ACYZP ACZBM ACZBN ACZUX ACZWT ADBBV ADCGK ADDNB ADFEC ADKIL ADMLS ADNMO ADOVH ADTCA ADVJH AEBAK AEBPU AEFOJ AEHGV AEMFK AEMTW AENCP AENEX AENGE AEUYN AFFUJ AFKQG AFKRA AFKRZ AFLOS AFLVW AFUTZ AFZFC AGABE AGBYD AGHGI AGJUD AGLWM AGQPQ AGTDA AHQXX AHRGI AIGNW AIHIV AIOIP AISIE AJ7 AJCYY AJPFC AJQAS AKZCZ ALIPV ALMA_UNASSIGNED_HOLDINGS ALSLI ALVPG ALWZO ANFVQ ANOYL AOWSX AQJOH ARABE ARAPS ARZZG ATUCA AUXHV AVDNQ AYIQA AZQEC BBLKV BBQHK BCGOX BENPR BESQT BGHMG BGLVJ BJBOZ BLZWO BMAJL BPHCQ BQFHP BVXVI C0O CAG CBIIA CCPQU CCQAD CCTKK CCUQV CDIZJ CFAFE CFBFF CGMFO CGQII CHEAL CJCSC COF CPGLG CRLPW CS3 DC4 DOHLZ DU5 DWQXO EBS ED0 EGQIC EJD FYUFA GNUQQ HCIFZ HG- HOVLH HSS HST HZ~ I.5 I.6 I.7 I.9 IH6 IOEEP IOO IPYYG IS6 I~P J36 J38 J3A JHPGK JOSPZ JPPIE JQKCU JRMXA K6V K7- KAFGG KCGVB KFECR L6V L98 LHUNA LW7 M-V M2M M7S M7~ M8. NIKVX NMFBF NZEOI O9- OYBOY P2P P62 PHGZM PHGZT PQQKQ PROAC PSYQQ PTHSS PYCCK Q2X RAMDC RCA RIG ROL RR0 S6- S6U SAAAG T9M UKHRP UT1 WFFJZ WQ3 WXS WXU WYP ZJOSE ZMEZD ZYDXJ ~A4 ~V1 ABGDZ AKMAY BSCLL PQGLB PRQQA PUEGO AAYXX AFFHD CITATION 3V. 7T9 7XB 8AL 8FK JQ2 M0N PKEHL PQEST PQUKI PRINS Q9U |
| ID | FETCH-LOGICAL-c3434-f98a01e70c42fbdc2b499ce370a9eed06cd89451f4311a6562ae083b7f4e6a9f3 |
| IEDL.DBID | K7- |
| ISSN | 1351-3249 |
| IngestDate | Thu Oct 02 10:19:50 EDT 2025 Wed Nov 12 04:41:31 EST 2025 Tue Nov 18 22:32:15 EST 2025 Sat Nov 29 01:32:20 EST 2025 Sun Aug 31 06:49:28 EDT 2025 Sun Jun 15 04:39:29 EDT 2025 |
| IsDoiOpenAccess | false |
| IsOpenAccess | true |
| IsPeerReviewed | true |
| IsScholarly | true |
| Issue | 4 |
| Language | English |
| License | https://www.cambridge.org/core/terms |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-c3434-f98a01e70c42fbdc2b499ce370a9eed06cd89451f4311a6562ae083b7f4e6a9f3 |
| Notes | ArticleID:00466 istex:44D629424E402F90AE4DE5400D2C3B88827F2801 PII:S1351324907004664 ark:/67375/6GQ-7G3PD4KT-7 ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| OpenAccessLink | https://research.brighton.ac.uk/en/publications/19a320ca-f3c6-47ae-8787-3882addfc1a0 |
| PQID | 216647282 |
| PQPubID | 30339 |
| PageCount | 25 |
| ParticipantIDs | proquest_miscellaneous_85686285 proquest_journals_216647282 crossref_citationtrail_10_1017_S1351324907004664 crossref_primary_10_1017_S1351324907004664 istex_primary_ark_67375_6GQ_7G3PD4KT_7 cambridge_journals_10_1017_S1351324907004664 |
| PublicationCentury | 2000 |
| PublicationDate | 20081001 |
| PublicationDateYYYYMMDD | 2008-10-01 |
| PublicationDate_xml | – month: 10 year: 2008 text: 20081001 day: 01 |
| PublicationDecade | 2000 |
| PublicationPlace | Cambridge, UK |
| PublicationPlace_xml | – name: Cambridge, UK – name: Cambridge |
| PublicationTitle | Natural language engineering |
| PublicationTitleAlternate | Nat. Lang. Eng |
| PublicationYear | 2008 |
| Publisher | Cambridge University Press |
| Publisher_xml | – name: Cambridge University Press |
| References | Hovy (S1351324907004664_ref16) 1988 S1351324907004664_ref24 S1351324907004664_ref25 S1351324907004664_ref22 S1351324907004664_ref23 S1351324907004664_ref29 S1351324907004664_ref26 S1351324907004664_ref20 S1351324907004664_ref42 S1351324907004664_ref21 S1351324907004664_ref40 S1351324907004664_ref41 Isabelle (S1351324907004664_ref19) 1984 Manning (S1351324907004664_ref28) 1999 Briscoe (S1351324907004664_ref8) 1993; 19 S1351324907004664_ref35 S1351324907004664_ref13 S1351324907004664_ref14 Mann (S1351324907004664_ref27) 1985 S1351324907004664_ref36 S1351324907004664_ref11 S1351324907004664_ref33 S1351324907004664_ref34 Habash (S1351324907004664_ref15) 2004 S1351324907004664_ref12 S1351324907004664_ref17 S1351324907004664_ref39 S1351324907004664_ref18 S1351324907004664_ref37 S1351324907004664_ref38 White (S1351324907004664_ref43) 2004 S1351324907004664_ref31 S1351324907004664_ref10 S1351324907004664_ref32 S1351324907004664_ref9 S1351324907004664_ref30 S1351324907004664_ref7 S1351324907004664_ref6 S1351324907004664_ref5 S1351324907004664_ref4 S1351324907004664_ref3 S1351324907004664_ref2 S1351324907004664_ref1 |
| References_xml | – ident: S1351324907004664_ref22 doi: 10.1007/11424574_11 – ident: S1351324907004664_ref39 – ident: S1351324907004664_ref13 doi: 10.1017/CBO9780511605611.007 – ident: S1351324907004664_ref12 – ident: S1351324907004664_ref18 doi: 10.3115/1117840.1117852 – start-page: 61 volume-title: Proceedings of the Third International Conference on Natural Language Generation (INLG'04) year: 2004 ident: S1351324907004664_ref15 – ident: S1351324907004664_ref35 doi: 10.3115/1641417.1641436 – volume-title: Generating Natural Language under Pragmatic Constraints year: 1988 ident: S1351324907004664_ref16 – ident: S1351324907004664_ref29 – start-page: 50 volume-title: Systemic Perspectives on Discourse: Selected Papers from the 9th International Systemics Workshop year: 1985 ident: S1351324907004664_ref27 – volume: 19 start-page: 25 year: 1993 ident: S1351324907004664_ref8 article-title: Generalised probabilistic LR parsing of natural language (corpora) with unification-based grammars publication-title: Computational Linguistics – ident: S1351324907004664_ref1 – ident: S1351324907004664_ref33 doi: 10.3115/992730.992739 – ident: S1351324907004664_ref26 – ident: S1351324907004664_ref30 – ident: S1351324907004664_ref5 – volume-title: Foundations of Statistical Natural Language Processing year: 1999 ident: S1351324907004664_ref28 – ident: S1351324907004664_ref3 – ident: S1351324907004664_ref10 doi: 10.1007/s11168-006-6327-9 – ident: S1351324907004664_ref34 – ident: S1351324907004664_ref37 doi: 10.1017/CBO9780511519857 – ident: S1351324907004664_ref7 – ident: S1351324907004664_ref32 – ident: S1351324907004664_ref17 – ident: S1351324907004664_ref38 – ident: S1351324907004664_ref40 – ident: S1351324907004664_ref25 doi: 10.3115/977180.977184 – ident: S1351324907004664_ref9 – volume-title: Machine Translation Today: The State of the Art year: 1984 ident: S1351324907004664_ref19 – ident: S1351324907004664_ref14 doi: 10.1109/64.294135 – ident: S1351324907004664_ref6 doi: 10.1075/idj.9.2-3.05bou – ident: S1351324907004664_ref21 – ident: S1351324907004664_ref42 doi: 10.3115/1073336.1073337 – ident: S1351324907004664_ref11 doi: 10.3115/1289189.1289273 – start-page: 182 volume-title: Proceedings of the Third International Conference on Natural Language Generation (INLG'04) year: 2004 ident: S1351324907004664_ref43 – ident: S1351324907004664_ref20 doi: 10.3115/100964.100979 – ident: S1351324907004664_ref31 doi: 10.3115/1219840.1219848 – ident: S1351324907004664_ref2 – ident: S1351324907004664_ref4 – ident: S1351324907004664_ref24 doi: 10.3115/974358.974361 – ident: S1351324907004664_ref41 doi: 10.21437/ICSLP.2002-303 – ident: S1351324907004664_ref36 doi: 10.1017/S1351324997001502 – ident: S1351324907004664_ref23 doi: 10.3115/974557.974596 |
| SSID | ssj0004174 |
| Score | 2.2121565 |
| Snippet | Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from traditional... Abstract Two important recent trends in natural language generation are (i) probabilistic techniques and (ii) comprehensive approaches that move away from... |
| SourceID | proquest crossref istex cambridge |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 431 |
| SubjectTerms | Automatic Text Generation Computational Linguistics Computer Modeling and Simulation Decision making Experiments Forecasting Language Natural language Natural Language Generation Natural Language Processing Probability Statistical Analysis Statistical methods Subject specialists Trends Weather Weather forecasting |
| Title | Automatic generation of weather forecast texts using comprehensive probabilistic generation-space models |
| URI | https://www.cambridge.org/core/product/identifier/S1351324907004664/type/journal_article https://api.istex.fr/ark:/67375/6GQ-7G3PD4KT-7/fulltext.pdf https://www.proquest.com/docview/216647282 https://www.proquest.com/docview/85686285 |
| Volume | 14 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVPQU databaseName: Advanced Technologies & Aerospace Database customDbUrl: eissn: 1469-8110 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004174 issn: 1351-3249 databaseCode: P5Z dateStart: 20010301 isFulltext: true titleUrlDefault: https://search.proquest.com/hightechjournals providerName: ProQuest – providerCode: PRVPQU databaseName: Computer Science Database customDbUrl: eissn: 1469-8110 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004174 issn: 1351-3249 databaseCode: K7- dateStart: 20010301 isFulltext: true titleUrlDefault: http://search.proquest.com/compscijour providerName: ProQuest – providerCode: PRVPQU databaseName: Engineering Database customDbUrl: eissn: 1469-8110 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004174 issn: 1351-3249 databaseCode: M7S dateStart: 20010301 isFulltext: true titleUrlDefault: http://search.proquest.com providerName: ProQuest – providerCode: PRVPQU databaseName: Linguistics Database customDbUrl: eissn: 1469-8110 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004174 issn: 1351-3249 databaseCode: CRLPW dateStart: 20010301 isFulltext: true titleUrlDefault: https://search.proquest.com/linguistics providerName: ProQuest – providerCode: PRVPQU databaseName: ProQuest Central customDbUrl: eissn: 1469-8110 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004174 issn: 1351-3249 databaseCode: BENPR dateStart: 20010301 isFulltext: true titleUrlDefault: https://www.proquest.com/central providerName: ProQuest – providerCode: PRVPQU databaseName: Psychology Database customDbUrl: eissn: 1469-8110 dateEnd: 20241207 omitProxy: false ssIdentifier: ssj0004174 issn: 1351-3249 databaseCode: M2M dateStart: 20010301 isFulltext: true titleUrlDefault: https://www.proquest.com/psychology providerName: ProQuest |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB5BlwMXylMsheID4oCwiJ2H7RMq0BapdLVAQRWXyHGctiratJvdws9nxnmsqkp74eKDY0eR5-Fx5vM3AK9EEXldupin3lk8oBjDdZkZ7pUo8ASSlFUgnv_5RU0m-vjYTDtsTtPBKnufGBx1WTv6R_5OioyYzrV8f3HJqWgUJVe7Chq3YSSkFKTmB4qvrkW2JMxUg45j3GD6pCYxRlMn9UVE754R38CKWuHaFjWi1f57w1OH7Wdv8z8__D7c6-JOttMqygO45WcPYbOv6cA6E38EpzvLRR1oXNlJYKQmwbG6Yn_aWJFhkIvr3SwYQUYaRrj5E0bA9Lk_bcHwjIrUBOLe5vprOHov51kovtM8hh97u0cfP_OuGgN3cRInvDLaRsKryCWyKkonCzwsOR-ryBrcaKPMldokqagwJBEWw0RpPcZ3haoSn1lTxU9gY1bP_FNgBWqO0AUlVVVS6qhAxagcnt3QNVun4jG8HYSRdzbV5C0eTeU3ZDeGqJdX7jpmcyqw8XvdlDfDlIuW1mPd4NdBCYaRdn5OeDiV5tn-11ztx9NPycFRrsaw1avA6rMH-Y_h5fAUbZgSM3bm62WT65Tu6ej02dr5W3BX9mS84jlsLOZL_wLuuKvFWTPfhtGH3cn023YwAWwP5SG16ju20_TXP-N0DKU |
| linkProvider | ProQuest |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LbxMxEB6VBgkulKcIBeoD9ICw2LftA4eqpQ8lRAEF6M14vd4WtcqWbELhR_EfmdlXVFXKrQeu3rW1sj_PY2fmG4BXfuo5mdmQx84adFCU4jJLFHfCT9EDibK8Ip7_OhSjkTw-VuM1-NvWwlBaZSsTK0GdFZb-kb8L_ISYzmXQJFAO3J9LdM_K90d7eJavg2D_w2T3kDcdBLgNozDiuZLG853wbBTkaWaDFA1860LhGYXKwUtsJlUU-zmqUd-gaRMYhzZJKvLIJUblIa67ffGTU5MqCuY2HTtuQU8mSqIc6O1-Ho6_LQsxa9pn6nrH0VJRbRiVOKppkMY8IpRPiOFgSeZwRSn26Hx_X9MNlcLb3_jPtuo-3Gssa7ZTX4UHsOamD2Gj7VrBGiH2CE53FvOiIqplJxXnNkGTFTm7rK1hhmY8IqqcM0qKKRlVBpwwSr2fudM63Z9RG56Kmri8ugxH-Wwdq9oLlY_hy41swRNYnxZT9xRYinfDlymFjUWUSS9F6OcWvVNUPsaKsA9vu8PXjdQodZ1xJ_Q1rPTBa_GhbcPdTi1EzldNedNNuaiJS1a9vF2BrnvTzM4o40_EOjn4pMVBON6LBhMt-rDZQm752R3e-rDVPUUpRaEnM3XFotQypkokGT9bOX8L7hxOPg718Gg02IS7QUs97D-H9fls4V7Abftr_qOcvWwuHoPvN43pf8WlZvg |
| linkToPdf | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V1LbxMxEB6VBCEuLU-RtlAfgAPC6r7tPSBUNaRUiaKACvTmer3eFrXKlmxC6U_j3zGzr6iqlFsPXL22tV5_8_B65huA127iWJkan4fWaDygxDGXaRRzK9wETyBBmpXE899HYjyWx8fxZA3-NrkwFFbZ6MRSUae5oX_ku54bEdO59HazOipi0h98vPzFqYAUXbQ21TQqhAzt9RWe3ooPh33c6jeeN_h0tP-Z1wUGuPEDP-BZLLXjWuGYwMuS1HgJ-v_G-sLRMdoOJzKpjIPQzdDKuho9H09bdFkSkQU20nHm47z3oCsjFJMOdPe_jiY_lkmZFQU0VcDj6LXEzZUq8VVTI7U5RC4fEdvBktjhhoHs0l7_uWUnSuM32PiPP9sjWK89brZXichjWLPTJ7DRVLNgtXJ7Cmd7i3leEtiy05KLmyDL8oxdVV4yQ_cekVbMGa2vYJQxcMooJH9mz6o0AEbleUrK4uLmNBz1trGsLDtUPINvd7Le59CZ5lP7AliCMuPKhK6TRZBKJ0GRyAyeWtEoaSP8HrxvgaBqbVKoKhJPqFu46YHTYEWZmtOdSotcrBryrh1yWRGarOr8tgRg21PPzikSUIQqOviixIE_6QfDIyV6sNXAb_naLfZ6sNM-Re1FV1J6avNFoWRIGUoy3Fw5fgceIGrV6HA83IKHXsNI7G5DZz5b2Jdw3_ye_yxmr2oZZHBy1_j9B9_bb64 |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Automatic+generation+of+Weather+forecast+texts+using+comprehensive+probabilistic+generation-space+models&rft.jtitle=Natural+language+engineering&rft.au=Belz%2C+Anja&rft.date=2008-10-01&rft.issn=1351-3249&rft.volume=14&rft.issue=4&rft.spage=431&rft.epage=455&rft_id=info:doi/10.1017%2FS1351324907004664&rft.externalDBID=NO_FULL_TEXT |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1351-3249&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1351-3249&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1351-3249&client=summon |