Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish

• URL: http://arxiv.org/abs/2502.20046v1
• Date: Thu, 27 Feb 2025 12:38:04 GMT
• Title: Polish-ASTE: Aspect-Sentiment Triplet Extraction Datasets for Polish
• Authors: Marta Lango, Borys Naglik, Mateusz Lango, Iwo Naglik,
• Abstract summary: We present two new datasets for ASTE containing customer opinions about hotels and purchased products expressed in Polish.<n>We also perform experiments with two ASTE techniques combined with two large language models for Polish to investigate their performance and the difficulty of the assembled datasets.<n>The new datasets are available under a permissive licence and have the same file format as the English datasets, facilitating their use in future research.
• Score: 1.6874375111244329
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Aspect-Sentiment Triplet Extraction (ASTE) is one of the most challenging and complex tasks in sentiment analysis. It concerns the construction of triplets that contain an aspect, its associated sentiment polarity, and an opinion phrase that serves as a rationale for the assigned polarity. Despite the growing popularity of the task and the many machine learning methods being proposed to address it, the number of datasets for ASTE is very limited. In particular, no dataset is available for any of the Slavic languages. In this paper, we present two new datasets for ASTE containing customer opinions about hotels and purchased products expressed in Polish. We also perform experiments with two ASTE techniques combined with two large language models for Polish to investigate their performance and the difficulty of the assembled datasets. The new datasets are available under a permissive licence and have the same file format as the English datasets, facilitating their use in future research.

Related papers

• Low-resource Information Extraction with the European Clinical Case Corpus [4.747950273856823]
  We present E3C-3.0, a multilingual dataset in the medical domain. The dataset includes both native texts in five languages and texts translated and projected from the English source into five target languages. A semi-automatic approach has been implemented, including automatic annotation projection.
  arXiv  Detail & Related papers  (2025-03-26T14:07:40Z)
• PSCon: Toward Conversational Product Search [55.94925947614474]
  We introduce a new CPS data collection protocol and present PSCon, a novel CPS dataset designed to assist product search via human-like conversations.<n>The dataset is constructed using a coached human-to-human data collection protocol and supports two languages and dual markets.
  arXiv  Detail & Related papers  (2025-02-19T17:05:42Z)
• Automated Question Generation on Tabular Data for Conversational Data Exploration [1.2574534342156884]
  We propose a system that recommends interesting questions in natural language based on relevant slices of a dataset in a conversational setting. We use our own fine-tuned variation of a pre-trained language model(T5) to generate natural language questions in a specific manner.
  arXiv  Detail & Related papers  (2024-07-10T08:07:05Z)
• 3AM: An Ambiguity-Aware Multi-Modal Machine Translation Dataset [90.95948101052073]
  We introduce 3AM, an ambiguity-aware MMT dataset comprising 26,000 parallel sentence pairs in English and Chinese. Our dataset is specifically designed to include more ambiguity and a greater variety of both captions and images than other MMT datasets. Experimental results show that MMT models trained on our dataset exhibit a greater ability to exploit visual information than those trained on other MMT datasets.
  arXiv  Detail & Related papers  (2024-04-29T04:01:30Z)
• OPSD: an Offensive Persian Social media Dataset and its baseline evaluations [2.356562319390226]
  This paper introduces two offensive datasets for Persian language. The first dataset comprises annotations provided by domain experts, while the second consists of a large collection of unlabeled data obtained through web crawling. The obtained F1-scores for the three-class and two-class versions of the dataset were 76.9% and 89.9% for XLM-RoBERTa, respectively.
  arXiv  Detail & Related papers  (2024-04-08T14:08:56Z)
• Multi3WOZ: A Multilingual, Multi-Domain, Multi-Parallel Dataset for Training and Evaluating Culturally Adapted Task-Oriented Dialog Systems [64.40789703661987]
  Multi3WOZ is a novel multilingual, multi-domain, multi-parallel ToD dataset. It is large-scale and offers culturally adapted dialogs in 4 languages. We describe a complex bottom-up data collection process that yielded the final dataset.
  arXiv  Detail & Related papers  (2023-07-26T08:29:42Z)
• Beyond Triplet: Leveraging the Most Data for Multimodal Machine Translation [53.342921374639346]
  Multimodal machine translation aims to improve translation quality by incorporating information from other modalities, such as vision. Previous MMT systems mainly focus on better access and use of visual information and tend to validate their methods on image-related datasets. This paper establishes new methods and new datasets for MMT.
  arXiv  Detail & Related papers  (2022-12-20T15:02:38Z)
• Multilingual Transformers for Product Matching -- Experiments and a New Benchmark in Polish [0.0]
  The paper shows that pre-trained, multilingual Transformer models, after fine-tuning, are suitable for solving the product matching problem. We tested multilingual mBERT and XLM-RoBERTa models in English on Web Data Commons. We prepared a new dataset entirely in Polish, which allows comparing the effectiveness of the pre-trained models.
  arXiv  Detail & Related papers  (2022-05-31T12:00:05Z)
• WANLI: Worker and AI Collaboration for Natural Language Inference Dataset Creation [101.00109827301235]
  We introduce a novel paradigm for dataset creation based on human and machine collaboration. We use dataset cartography to automatically identify examples that demonstrate challenging reasoning patterns, and instruct GPT-3 to compose new examples with similar patterns. The resulting dataset, WANLI, consists of 108,357 natural language inference (NLI) examples that present unique empirical strengths.
  arXiv  Detail & Related papers  (2022-01-16T03:13:49Z)
• Cross-Lingual Low-Resource Set-to-Description Retrieval for Global E-Commerce [83.72476966339103]
  Cross-lingual information retrieval is a new task in cross-border e-commerce. We propose a novel cross-lingual matching network (CLMN) with the enhancement of context-dependent cross-lingual mapping. Experimental results indicate that our proposed CLMN yields impressive results on the challenging task.
  arXiv  Detail & Related papers  (2020-05-17T08:10:51Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.