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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Datasets for "ESNLIR: A Spanish Multi-Genre Dataset with Causal Relationships"

Authors: Rodriguez Portela, Johan David; Manrique Piramanrique, Rubén Francisco; Perez Terán, Nicolás;

Datasets for "ESNLIR: A Spanish Multi-Genre Dataset with Causal Relationships"

Abstract

ESNLIR: A Spanish Multi-Genre Dataset with Causal Relationships These are the datasets for the paper ESNLIR: A Spanish Multi-Genre Dataset with Causal Relationships. Dataset dictionary This repository contains the splits that resulted from the research project "ESNLIR: A Spanish Multi-Genre Dataset with Causal Relationships". All the splits are in JSONL format and have the same fields per example: sentence_1: First sentence of the pair. sentence_2: Second sentence of the pair. connector: Linking phrase used to extract pair. connector_type: NLI label, between "contrasting", "entailment", "reasoning" or "neutral" extraction_strategy: "linking_phrase" for "contrasting", "entailment", "reasoning" and "none" for neutral. distance: How many sentences before the connector is the sentence_1 sentence_1_position: Number of sentence for sentence_1 in the source document sentence_1_paragraph: Number of paragraph for sentence_1 in the source document sentence_2_position: Number of sentence for sentence_2 in the source document sentence_2_paragraph: Number of paragraph for sentence_2 in the source document id: Unique identifier for the example dataset: Source corpus of the pair. Metadata of corpus, including source can be found in dataset_metadata.xlsx. genre: Writing genre of the dataset. domain: Domain genre of the dataset. Example: {"sentence_1":"sefior Bcajavides no es moderado, tampoco lo convertirse e\u00f1 declarada divergencia de miras polileido en griego","sentence_2":"era mayor claricomentarios, as\u00ed de los peri\u00f3dicos como de los homes dado \u00e1 la voluntad de los hombres, sin que sobreticas","connector":"por consiguiente,","connector_type":"reasoning","extraction_strategy":"linking_phrase","distance":1.0,"sentence_1_paragraph":4,"sentence_1_position":86,"sentence_2_paragraph":4,"sentence_2_position":87,"id":"esnews__spanish_pd_news__531537","dataset":"esnews__spanish_pd_news","genre":"news","domain":"spanish_public_domain_news"} Dataset files ESNLIR_datasets.zip: Contains the splits used for BERT-based model training, validation and testing, including stress test splits. labeled_final_dataset.jsonl: Is the final test dataset with 974 examples selected by human majority label matching the original linking phrase label.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average