In this paper, we describe the approach of the ItaliaNLP Lab team to native language identification and discuss the results we submitted as participants to the essay track of NLI Shared Task 2017. We introduce for the first time a 2-stacked sentencedocument architecture for native language identification that is able to exploit both local sentence information and a wide set of general-purpose features qualifying the lexical and grammatical structure of the whole document. When evaluated on the official test set, our sentence-document stacked architecture obtained the best result among all the participants of the essay track with an F1 score of 0.8818.
Stacked Sentence-Document Classifier Approach for Improving Native Language Identification
Cimino A;Dell'Orletta F
2017
Abstract
In this paper, we describe the approach of the ItaliaNLP Lab team to native language identification and discuss the results we submitted as participants to the essay track of NLI Shared Task 2017. We introduce for the first time a 2-stacked sentencedocument architecture for native language identification that is able to exploit both local sentence information and a wide set of general-purpose features qualifying the lexical and grammatical structure of the whole document. When evaluated on the official test set, our sentence-document stacked architecture obtained the best result among all the participants of the essay track with an F1 score of 0.8818.| Campo DC | Valore | Lingua |
|---|---|---|
| dc.authority.orgunit | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | - |
| dc.authority.people | Cimino A | it |
| dc.authority.people | Dell'Orletta F | it |
| dc.collection.id.s | 71c7200a-7c5f-4e83-8d57-d3d2ba88f40d | * |
| dc.collection.name | 04.01 Contributo in Atti di convegno | * |
| dc.contributor.appartenenza | Istituto di linguistica computazionale "Antonio Zampolli" - ILC | * |
| dc.contributor.appartenenza.mi | 918 | * |
| dc.date.accessioned | 2024/02/20 04:10:53 | - |
| dc.date.available | 2024/02/20 04:10:53 | - |
| dc.date.issued | 2017 | - |
| dc.description.abstracteng | In this paper, we describe the approach of the ItaliaNLP Lab team to native language identification and discuss the results we submitted as participants to the essay track of NLI Shared Task 2017. We introduce for the first time a 2-stacked sentencedocument architecture for native language identification that is able to exploit both local sentence information and a wide set of general-purpose features qualifying the lexical and grammatical structure of the whole document. When evaluated on the official test set, our sentence-document stacked architecture obtained the best result among all the participants of the essay track with an F1 score of 0.8818. | - |
| dc.description.affiliations | Istituto di Linguistica Computazionale "A. Zampolli" | - |
| dc.description.allpeople | Cimino, A; Dell'Orletta, F | - |
| dc.description.allpeopleoriginal | Cimino A., Dell'Orletta F. | - |
| dc.description.fulltext | none | en |
| dc.description.numberofauthors | 2 | - |
| dc.identifier.uri | https://hdl.handle.net/20.500.14243/341662 | - |
| dc.language.iso | eng | - |
| dc.relation.conferencedate | 2017 | - |
| dc.relation.conferencename | Workshop on Innovative Use of NLP for Building Educational Applications | - |
| dc.relation.conferenceplace | Copenaghen, Danimaca | - |
| dc.relation.firstpage | 430 | - |
| dc.relation.lastpage | 437 | - |
| dc.relation.numberofpages | 8 | - |
| dc.subject.keywords | Native Language Identification | - |
| dc.subject.singlekeyword | Native Language Identification | * |
| dc.title | Stacked Sentence-Document Classifier Approach for Improving Native Language Identification | en |
| dc.type.driver | info:eu-repo/semantics/conferenceObject | - |
| dc.type.full | 04 Contributo in convegno::04.01 Contributo in Atti di convegno | it |
| dc.type.miur | 273 | - |
| dc.type.referee | Sì, ma tipo non specificato | - |
| dc.ugov.descaux1 | 382167 | - |
| iris.orcid.lastModifiedDate | 2024/04/04 16:00:15 | * |
| iris.orcid.lastModifiedMillisecond | 1712239215402 | * |
| iris.sitodocente.maxattempts | 1 | - |
| Appare nelle tipologie: | 04.01 Contributo in Atti di convegno | |
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