4 papers
AutoSpecNER: A Fine-Grained Named Entity Recognition Dataset for Vehicle Specification Extraction
Jordan Lee, Filippos Ventirozos, Abdirahman Abdullahm +3
Vehicle advertisements contain rich specification information, but automotive NER resources remain limited. We introduce AutoSpecNER, an expert-annotated dataset for fine-grained e…
Exploring Zero-Shot ACSA with Unified Meaning Representation in Chain-of-Thought Prompting
Filippos Ventirozos, Peter Appleby, Matthew Shardlow
Aspect-Category Sentiment Analysis (ACSA) provides granular insights by identifying specific themes within reviews and their associated sentiment. While supervised learning approac…
Are You Sure You're Positive? Consolidating Chain-of-Thought Agents with Uncertainty Quantification for Aspect-Category Sentiment Analysis
Filippos Ventirozos, Peter Appleby, Matthew Shardlow
Aspect-category sentiment analysis provides granular insights by identifying specific themes within product reviews that are associated with particular opinions. Supervised learnin…
Shifting NER into High Gear: The Auto-AdvER Approach
Filippos Ventirozos, Ioanna Nteka, Tania Nandy +3
This paper presents a case study on the development of Auto-AdvER, a specialised named entity recognition schema and dataset for text in the car advertisement genre. Developed with…