The official fork of THoR Chain-of-Thought framework, enhanced and adapted for Emotion Cause Analysis (ECAC-2024)
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Updated
Jul 13, 2024 - Python
The official fork of THoR Chain-of-Thought framework, enhanced and adapted for Emotion Cause Analysis (ECAC-2024)
This repository is for the paper UAlberta at SemEval-2023 Task 1: Context Augmentation and Translation for Multilingual Visual Word Sense Disambiguation. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023). Association for Computational Linguistics.
An implementation of a full named-entity evaluation metrics based on SemEval'13 Task 9 - not at tag/token level but considering all the tokens that are part of the named-entity
The supplementary sevice over THoR Chain-of-Thought framework as part of SemEval-2024 Task 3 paper
Submission for SemEval 2024 - Task 8 (Subtask A)
Ekphrasis is a text processing tool, geared towards text from social networks, such as Twitter or Facebook. Ekphrasis performs tokenization, word normalization, word segmentation (for splitting hashtags) and spell correction, using word statistics from 2 big corpora (english Wikipedia, twitter - 330mil english tweets).
Our submission to the SemEval2019 shared task on Hyperpartisan News Detection.
[WWW 2022] KnowPrompt: Knowledge-aware Prompt-tuning with Synergistic Optimization for Relation Extraction
Sarcasm is a term that refers to the use of words to mock, irritate, or amuse someone. It is commonly used on social media. The metaphorical and creative nature of sarcasm presents a significant difficulty for sentiment analysis systems based on affective computing. The technique and results of our team, UTNLP, in the SemEval-2022 shared task 6 …
TüReuth Legal Code for SemEval 2023 Task 6: LegalAI.
Winner system (DAMO-NLP) of SemEval 2022 MultiCoNER shared task over 10 out of 13 tracks.
Sentiment Analysis: Deep Bi-LSTM+attention model
Deep-learning models of NTUA-SLP team submitted in SemEval 2018 tasks 1, 2 and 3.
Compare BERT-based models for document-level sentiment analysis using the SemEval 2017 Twitter dataset.
Semantic Textual Similarity (STS) measures the degree of equivalence in the underlying semantics of paired snippets of text.
Code of IIE-NLP-Eyas Team for ReCAM (Task 4) @SemEval2021 (https://arxiv.org/abs/2102.12777)
The Codebase for Quasi-Attention BERT Model for TABSA Tasks (AAAI '21)
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