datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
SemCor
Dataset Card for SemCor
Dataset Summary
SemCor 3.0 was automatically created from SemCor 1.6 by mapping WordNet 1.6 to
WordNet 3.0 senses. SemCor 1.6 was created and is property of Princeton
University.
Some (few) word senses from WordNet 1.6 were dropped, and therefore they cannot
be retrieved anymore in the 3.0 database. A sense of 0 (wnsn=0) is used to
symbolize a missing sense in WordNet 3.0.
The automatic mapping was performed within the Language and Information… See the full description on the dataset page: https://huggingface.co/datasets/thesofakillers/SemCor.SemCorwsd_semcor
Dataset Card for "wsd_semcor"
More Information needed
SemCor
Dataset Card for "SemCor – sense-tagged English corpus"
Description
This dataset is derived from the wsd_semcor dataset, originally hosted on Hugging Face. It has been preprocessed for tasks related to Word Sense Disambiguation (WSD) and WordNet integration.
Preprocessing
The original text data underwent the following preprocessing steps:
Text splitting into individual words (lemmas).
TF-IDF (Term Frequency-Inverse Document Frequency) analysis to understand… See the full description on the dataset page: https://huggingface.co/datasets/MarkChen1214/SemCor.WSD_DATASET_FEWS_SEMCOR
FEWS and Semcor Dataset for Word Sense Disambiguation (WSD)
This repository contains a formatted and cleaned version of the FEWS and Semcor dataset, specifically arranged for model fine-tuning for Word Sense Disambiguation (WSD) tasks.
Dataset Description
The FEWS and Semcor dataset has been preprocessed and formatted to be directly usable for training and fine-tuning language models for word sense disambiguation. Each ambiguous word in the context is enclosed with <WSD>… See the full description on the dataset page: https://huggingface.co/datasets/deshanksuman/WSD_DATASET_FEWS_SEMCOR.Chinese-Wordnet-SemCor
Chinese Wordnet SemCor
Dataset Summary
This dataset is designed for the task of Word Sense Disambiguation (WSD) for common Chinese words, specifically focusing on words identified as "difficult" (having more than 10 senses) within Chinese Wordnet (CWN) 2.0. It originates from the annotation dataset described in Section 3.1 of the paper "Resolving Regular Polysemy in Named Entities."
The original dataset consisted of 28,836 example sentences where a target "difficult" word… See the full description on the dataset page: https://huggingface.co/datasets/lopentu/Chinese-Wordnet-SemCor.wsd_fr_wngt_semcor_translated_aligned_v2
Dataset Card for "wsd_fr_wngt_semcor_translated_aligned_v2"
More Information needed
SemCorrVLM_raw
SemCorrVLM_raw
wsd_fr_wngt_semcor_translated_aligned_all_v1
Dataset Card for "wsd_fr_wngt_semcor_translated_aligned_all_v1"
More Information needed
wsd_fr_wngt_semcor_translated_aligned
Dataset Card for "wsd_fr_wngt_semcor_translated_aligned"
More Information needed
selection_semcorgeneration_semcor