Update README.md

README.md

@@ -1,6 +1,110 @@
 ---
-license: creativeml-openrail-m
+license: cc-by-nc-sa-4.0
 language:
 - es
 pretty_name: 'EsCoLA: Spanish Corpus of Linguistic Acceptability'
----
+---
+Introduction
+
+The Spanish Corpus of Linguistic Acceptability (EsCoLA) includes 11,174 sentences taken from linguistic literature with a binary annotation made by the original authors themselves. The work is inspired by CoLA: https://nyu-mll.github.io/CoLA/#
+
+Paper
+
+Núria Bel, Marta Punsola, Valle Ruiz-Fernández, 2024, EsCoLA: Spanish Corpus of Linguistic Acceptability. Joint International Conference on Computational Linguistics, Language Resources and Evaluation LREC-COLING 2024. Torino. Italy.
+
+Download
+
+The corpus has a CC-BY 4.0 license. Download EsCoLA inDomain train and dev datasets, plus human annotation, from https://github.com/nuriabel/LUTEST/ For EsCoLA outDomain dataset and EsCoLA inDomain test data, please contact [email protected].
+
+Data format
+
+EsCoLA dataset is split into two subsets: an in-domain subset (InDomain) with 10,567 sentences, and an out-of-domain subset (OutDomain) with 607 sentences. The in-domain subset has been split five times into train/dev/test sections:
+
+train: 8454 sentences
+dev:   1053 sentences
+test:  1060 sentences 
+
+And the out-of-domain subset is split into dev/test sections. The test sets are not made public.
+
+For the in-domain subset, each line in the .tsv files consists of 11 tab-separated columns:
+
+Column 1: a unique ID
+Column 2: the source of the sentence
+Column 3: the acceptability judgment label from the source (0=unacceptable, 1=acceptable)
+Column 4: the source's annotation (* for the unacceptable sentences)
+Columns 5, 6 and 7: the human annotations
+Column 8: the human annotations' median
+Column 9: the sentence
+Column 10: the category of the linguistic phenomenon the sentence is an example of
+Column 11: the split to which the sentence belongs
+
+For the out-of-domain, each line in the .tsv file consists of 6 tab-separated columns:
+
+Column 1: a unique ID
+Column 2: the source of the sentence
+Column 3: the acceptability judgment label from the source (0=unacceptable, 1=acceptable)
+Column 4: the source's annotation (* for the unacceptable sentences)
+Column 5: the sentence
+Column 6: the category of the linguistic phenomenon the sentence is an example of
+Corpus Sample
+
+In-domain:
+
+ID Source Label Source_annotation Annotator_1 Annotator_2 Annotator_3 Human_annotation_median Sentence Category Split 
+EsCoLA_5681 GDE35 1 1 0 1 1 ¿Opinaron si debían hacerlo? 7 train 
+EsCoLA_8872 GDE51 1 1 1 1 1 ¿Quién ha llamado? 7 train EsCoLA_5661 
+GDE35 1 1 0 0 0 No se sabe donde ir. 7 train 
+EsCoLA_7328 GDE42 0 * 0 1 1 1 Sólo tenía una peseta, y aquel tipo me pedía doscientos. 14 train
+
+Out-of-domain:
+
+ID Source Label Source annotation Sentence Category 
+OD_1 ng34 1 El camino bordea el río. 1 
+OD_2 ng34 1 Las aves vuelan. 1 
+OD_3 ng34 1 Pepe tiene dinero. 1 
+OD_4 ng34 1 Tengo hambre. 1 
+OD_5 ng34 0 * Dudo tu solución. 1
+
+Processing
+
+During gathering of the data and processing, some sentences from the source documents may have been omitted or altered. We discarded examples marking dubious acceptability with "?" or other signs, but those examples that included acceptability alternations were taken by creating the two versions: the acceptable and the unacceptable sentence. Finally, the examples that were not full sentences, that is, that contain no main verb, were manually edited to add a neutral verb to convert them into sentences, while keeping the acceptability value.
+
+Sources
+
+InDomain: Demonte and Bosque (1999)
+OutDomain: RAE (2009), Palencia and Aragonés (2007) Díaz and Yagüe (2019)
+
+Annotation The dataset has been manually annotated with 14 linguistic phenomena.
+
+1. Simple
+2. Predicative
+3. Adjuncts
+4. Argument types
+5. Argument alternation
+6. Binding pronouns
+7. Wh-phenomena
+8. Complement clauses
+9. Modal, negation, periphrasis and auxiliaries
+10. Infinitive embedded VPs and referential phenomena
+11. Complex NPs and APs
+12. S-Syntax
+13. Determiners, quantifiers, comparative and superlative constructions
+14. Spanish phenomena The Spanish phenomena have been classified into 6 categories:
+14.1. Agreement in nominal constructions
+14.2. Subjunctive mode and tense
+14.3. Spurious preposition for completive clauses ('dequeismo')
+14.4. Subject ellipsis
+14.5. Pronominal cliticization
+14.6. Ser/estar copula selection
+
+Citation
+
+Please, if you use the dataset cite the following papers:
+
+Alex Warstadt, Amanpreet Singh, and Samuel R. Bowman. 2018. Neural network acceptability judgments. arXiv preprint arXiv:1805.12471.
+
+Núria Bel, Marta Punsola, Valle Ruiz-Fernández, 2024, EsCoLA: Spanish Corpus of Linguistic Acceptability. Joint International Conference on Computational Linguistics, Language Resources and Evaluation LREC-COLING 2024. Torino. Italy.
+
+Disclaimer
+
+The dataset has been made by copying the examples from published works that are protected by copyright. According to Spanish law, we have respected the copyright because the number of elements taken represent less than a 10% of the whole work, and the number of items copied is justified by the aims of research.