SweNLI 1.0
type: Dataset
distribution: Landing page for the dataset
description: I. IDENTIFYING INFORMATION Title* SweNLI Subtitle Created by* Felix Morger (felix.morger@gu.se), Lars Borin, Aleksandrs Berdicevskis (Gothenburg University) Publisher(s)* Språkbanken Text (sb-info@svenska.gu.se) Link(s) / permanent identifier(s)* https://spraakbanken.gu.se/en/resources/superlim License(s)* CC BY 4.0 Abstract* A Swedish NLI dataset. Train and dev are machine-translated from the English MNLI dataset, test is manually translated and adapted from the English Fracas dataset. Funded by* Vinnova (grants no. 2020-02523, 2021-04165) Cite as Related datasets Part of the SuperLim collection. Similar to SuperGLUE diagnostic dataset. II. USAGE Key applications Machine Learning, Inference, Entailment, Evaluation of language models, Diagnostics Intended task(s)/usage(s) Natural language inference. Recommended evaluation measures Krippendorff's Alpha (the official SuperLim measure), Accuracy Dataset function(s) Training, testing Recommended split(s) Train, dev, test (provided) III. DATA Primary data* Text Language* Swedish. Train and dev: machine-translated Dataset in numbers* Train: 392704 items, dev: 9815 items, test: 305 items Nature of the content* Inference problems, where a relation between a premise and a hypothesis has to be detected: entailment, neutral or contradiction. Format* JSON Lines, with one item per line. Each item contains an id, a premise (in test, the premise may contain several sentences, but is still represented as a single item), a hypothesis and a label. The dataset is also available as a tsv with self-explanatory column names. For test, an additional file is provided where the items can be matched with the original Fracas items Data source(s)* Train and dev: see [1]. Machine translated from English to Swedish using OPUS-MT. Test: see [2] and 'Data collection methods'. Data collection method(s)* Train and dev: see [1]. Test: SweFracas (part of the SuperLim 1.0). The original English Fracas [2] was converted to html and edited by Bill MacCar…
modified: 2023-03-30T00:00:00Z
issued: 2024-01-01T00:00:00Z
publisher: University of Gothenburg
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Morger, Felix
    type: Agent
    type: PrivateIndividual(s)
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Borin, Lars
    type: Agent
    type: PrivateIndividual(s)
qualified attribution: Attribution
  had role: principalInvestigator
  agent: Berdicevskis, Aleksandrs
    type: Agent
    type: PrivateIndividual(s)
keyword: Language Technology (Computational Linguistics)
keyword: corpus
language: SWE

Landing page for the dataset
type: Distribution
title: Landningssida för datasetet @sv
access URL: SweNLI 1.0
availability: stable

University of Gothenburg
type: Agent
name: Göteborgs universitet @sv
type: Academia-ScientificOrganisation
source: 01tm6cn81