Results 41 to 50 of about 1,142,269 (203)

Collective List-Only Entity Linking: A Graph-Based Approach

IEEE Access, 2018
List-only entity linking (EL) is the task of mapping ambiguous mentions in texts to target entities in a group of entity lists. Different from traditional EL task, which leverages rich semantic relatedness in knowledge bases to improve linking accuracy ...
Weixin Zeng, Xiang Zhao, Jiuyang Tang, Haichuan Shang   +3 more
doaj   +1 more source

PWNC: A Large-Scale Persian Corpus for Joint WSD and NER Using Semi-Supervised and Supervised Learning [PDF]

Journal of Artificial Intelligence and Data Mining
Word Sense Disambiguation (WSD) is a longstanding challenge in natural language processing, particularly in morphologically rich and low-resource languages such as Persian.
Arash Keshtkar, Saeedeh Sadat Sadidpour, Hossien Shirazi   +2 more
doaj   +1 more source

Graph Ranking for Collective Named Entity Disambiguation [PDF]

Proceedings of the 52nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2014
Named Entity Disambiguation (NED) refers to the task of mapping different named entity mentions in running text to their correct interpretations in a specific knowledge base (KB). This paper presents a collective disambiguation approach using a graph model.
Ayman Alhelbawy, Robert J. Gaizauskas
openaire   +1 more source

Abstractive Text Summarization: Enhancing Sequence-to-Sequence Models Using Word Sense Disambiguation and Semantic Content Generalization

Computational Linguistics, 2021
Nowadays, most research conducted in the field of abstractive text summarization focuses on neural-based models alone, without considering their combination with knowledge-based approaches that could further enhance their efficiency.
Panagiotis Kouris, Georgios Alexandridis, Andreas Stafylopatis   +2 more
doaj   +1 more source

Improving the Performance of Vietnamese–Korean Neural Machine Translation with Contextual Embedding

Applied Sciences, 2021
With the recent evolution of deep learning, machine translation (MT) models and systems are being steadily improved. However, research on MT in low-resource languages such as Vietnamese and Korean is still very limited.
Van-Hai Vu, Quang-Phuoc Nguyen, Ebipatei Victoria Tunyan, Cheol-Young Ock   +3 more
doaj   +1 more source

The PRIMA Thesaurus for Materials Science and Engineering

Advanced Engineering Materials, EarlyView.
The PRIMA Thesaurus is a structured vocabulary designed to improve how materials science data is described and shared. Developed with input from multiple experts, it enables clear documentation of research workflows, data exchange, and reuse across platforms.
Rossella Aversa, Alexey Boubnov, Dario De Angelis, Catriona Eschke, Maximilian Kabbe, Felix Kraus, Mirco Panighel, Richard Thelen, Davide Valentinis   +8 more
wiley   +1 more source

Towards large-scale, open-domain and ontology-based named entity classification [PDF]

, 2005
Cimiano P, Völker J. Towards large-scale, open-domain and ontology-based named entity classification. In: Angelova G, Bontcheva K, Mitkov R, Nicolov N, eds.
Völker, Johanna, Angelova, G., Mitkov, R., Nicolov, N., Bontcheva, K., Cimiano, Philipp ; https://orcid.org/   +5 more
core  

Multimodal Human–Robot Interaction Using Human Pose Estimation and Local Large Language Models

Advanced Robotics Research, EarlyView.
A multimodal human–robot interaction framework integrates human pose estimation (HPE) and a large language model (LLM) for gesture‐ and voice‐based robot control. Speech‐to‐text (STT) enables voice command interpretation, while a safety‐aware arbitration mechanism prioritizes gesture input for rapid intervention.
Nasiru Aboki, Ilche Georgievski, Marco Aiello   +2 more
wiley   +1 more source

Accelerating the Discovery of Proton Conducting Electrolytes via Machine Learning‐Enabled Literature Mining

Advanced Intelligent Discovery, EarlyView.
An end‐to‐end knowledge discovery framework is established to automate high‐precision property extraction from small, specialized literature corpora. Utilizing a domain‐specific bidirectional encoder representation from a transformer model and data augmentation, the system accurately extracts and structures electrolyte performance data, ultimately ...
Gaheun Shin, Seongho Lee, Seulchan Kim, Ho‐Il Ji, Joonhee Kang   +4 more
wiley   +1 more source

ANERD: A Large-Scale Arabic Corpus for Named Entity Recognition and Disambiguation

Data
Arabic NER and NED research is limited by the lack of large-scale public datasets that support both tasks with validated entity links and difficulty-aware evaluation. In this paper, we propose ANERD, a large-scale Arabic corpus and benchmark for NER/NED,
Madawi Saqer Alotaibi, Mohamed El Bachir Menai   +1 more
doaj   +1 more source