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Found 4 papers, 2 papers with code
Zshot: An Open-source Framework for Zero-Shot Named Entity Recognition and Relation Extraction
Additionally, we have designed our framework to support the industry with readily available APIs for production under the standard SpaCy NLP pipeline.
Learning to Rank from Relevance Judgments Distributions
Learning to Rank (LETOR) algorithms are usually trained on annotated corpora where a single relevance label is assigned to each available document-topic pair.
Neural Feature Selection for Learning to Rank
LEarning TO Rank (LETOR) is a research area in the field of Information Retrieval (IR) where machine learning models are employed to rank a set of items.
A Semi-Automated Approach for Information Extraction, Classification and Analysis of Unstructured Data
In this paper, we show how Quantitative Narrative Analysis and simple Natural Language Processing techniques apply to the extraction and categorization of data in a sample case study of the Diary of the former President of the Italian Republic (PoR), Giorgio Napolitano.
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