Automatic grammatical tagger for a Spanish–Mixtec parallel corpus
In this work, we developed the first intelligent automatic grammatical tagger for a Spanish–Mixtec parallel corpus in Mexico. The proposed tagger consists of multiple phases. We started by collecting a Spanish–Mixtec parallel corpus of 12,300 sentences. Then, we tokenized the corpus at the word leve...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-02-01
|
| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2352711024003558 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849721775449964544 |
|---|---|
| author | Hermilo Santiago-Benito Diana-Margarita Córdova-Esparza Noé-Alejandro Castro-Sánchez Juan Terven Julio-Alejandro Romero-González Teresa García-Ramirez |
| author_facet | Hermilo Santiago-Benito Diana-Margarita Córdova-Esparza Noé-Alejandro Castro-Sánchez Juan Terven Julio-Alejandro Romero-González Teresa García-Ramirez |
| author_sort | Hermilo Santiago-Benito |
| collection | DOAJ |
| description | In this work, we developed the first intelligent automatic grammatical tagger for a Spanish–Mixtec parallel corpus in Mexico. The proposed tagger consists of multiple phases. We started by collecting a Spanish–Mixtec parallel corpus of 12,300 sentences. Then, we tokenized the corpus at the word level, removing empty lines, duplicate sentences, and empty terms from the texts, followed by identifying word units, such as multiword and compound words, and defined word classes, specifying mandatory, recommended, and optional characteristics according to the EAGLES group. We established a standard for annotating words based on EAGLES, considering three elements: attribute, value, and code. Finally, we proposed a synthetic Mixtec tag using GPT-4, GPT-4o, and a manual tag using alignment, conditional random fields (CRF) and BERT models. We manually annotated 600 sentences for a total of 2800 words and semi-automatically annotated 3000 more sentences using GPT-4o with few-shot prompting. We trained multiple models for automatic grammatical tagging, achieving a precision of 0.74 and a recall of 0.80. |
| format | Article |
| id | doaj-art-ad57cdcd71f6401cb6b5279570828b62 |
| institution | DOAJ |
| issn | 2352-7110 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Elsevier |
| record_format | Article |
| series | SoftwareX |
| spelling | doaj-art-ad57cdcd71f6401cb6b5279570828b622025-08-20T03:11:33ZengElsevierSoftwareX2352-71102025-02-012910198510.1016/j.softx.2024.101985Automatic grammatical tagger for a Spanish–Mixtec parallel corpusHermilo Santiago-Benito0Diana-Margarita Córdova-Esparza1Noé-Alejandro Castro-Sánchez2Juan Terven3Julio-Alejandro Romero-González4Teresa García-Ramirez5Facultad de Informática, Universidad Autonoma de Querétaro, Av. de las Ciencias S/N, Campus Juriquilla, C.P. 76230, Querétaro, MexicoFacultad de Informática, Universidad Autonoma de Querétaro, Av. de las Ciencias S/N, Campus Juriquilla, C.P. 76230, Querétaro, Mexico; Corresponding author.Centro Nacional de Investigación y Desarrollo Tecnológico, Tecnológico Nacional de Mexico, Interior Internado Palmira S/N, Palmira, C.P. 62493, Cuernavaca, Morelos, MexicoCICATA - Unidad Querétaro, Instituto Politécnico Nacional, Cerro Blanco No. 141, Col. Colinas del Cimatario, C.P. 76090, Querétaro, MexicoFacultad de Informática, Universidad Autonoma de Querétaro, Av. de las Ciencias S/N, Campus Juriquilla, C.P. 76230, Querétaro, MexicoFacultad de Informática, Universidad Autonoma de Querétaro, Av. de las Ciencias S/N, Campus Juriquilla, C.P. 76230, Querétaro, MexicoIn this work, we developed the first intelligent automatic grammatical tagger for a Spanish–Mixtec parallel corpus in Mexico. The proposed tagger consists of multiple phases. We started by collecting a Spanish–Mixtec parallel corpus of 12,300 sentences. Then, we tokenized the corpus at the word level, removing empty lines, duplicate sentences, and empty terms from the texts, followed by identifying word units, such as multiword and compound words, and defined word classes, specifying mandatory, recommended, and optional characteristics according to the EAGLES group. We established a standard for annotating words based on EAGLES, considering three elements: attribute, value, and code. Finally, we proposed a synthetic Mixtec tag using GPT-4, GPT-4o, and a manual tag using alignment, conditional random fields (CRF) and BERT models. We manually annotated 600 sentences for a total of 2800 words and semi-automatically annotated 3000 more sentences using GPT-4o with few-shot prompting. We trained multiple models for automatic grammatical tagging, achieving a precision of 0.74 and a recall of 0.80.http://www.sciencedirect.com/science/article/pii/S2352711024003558POS taggingGrammatical categoryLow-resource languagePart of speech tagging |
| spellingShingle | Hermilo Santiago-Benito Diana-Margarita Córdova-Esparza Noé-Alejandro Castro-Sánchez Juan Terven Julio-Alejandro Romero-González Teresa García-Ramirez Automatic grammatical tagger for a Spanish–Mixtec parallel corpus SoftwareX POS tagging Grammatical category Low-resource language Part of speech tagging |
| title | Automatic grammatical tagger for a Spanish–Mixtec parallel corpus |
| title_full | Automatic grammatical tagger for a Spanish–Mixtec parallel corpus |
| title_fullStr | Automatic grammatical tagger for a Spanish–Mixtec parallel corpus |
| title_full_unstemmed | Automatic grammatical tagger for a Spanish–Mixtec parallel corpus |
| title_short | Automatic grammatical tagger for a Spanish–Mixtec parallel corpus |
| title_sort | automatic grammatical tagger for a spanish mixtec parallel corpus |
| topic | POS tagging Grammatical category Low-resource language Part of speech tagging |
| url | http://www.sciencedirect.com/science/article/pii/S2352711024003558 |
| work_keys_str_mv | AT hermilosantiagobenito automaticgrammaticaltaggerforaspanishmixtecparallelcorpus AT dianamargaritacordovaesparza automaticgrammaticaltaggerforaspanishmixtecparallelcorpus AT noealejandrocastrosanchez automaticgrammaticaltaggerforaspanishmixtecparallelcorpus AT juanterven automaticgrammaticaltaggerforaspanishmixtecparallelcorpus AT julioalejandroromerogonzalez automaticgrammaticaltaggerforaspanishmixtecparallelcorpus AT teresagarciaramirez automaticgrammaticaltaggerforaspanishmixtecparallelcorpus |