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Found 20 papers, 1 papers with code
AskMe: A LAPPS Grid-based NLP Query and Retrieval System for Covid-19 Literature
In a recent project, the Language Application Grid was augmented to support the mining of scientific publications.
Evaluating Retrieval for Multi-domain Scientific Publications
This paper provides an overview of the xDD/LAPPS Grid framework and provides results of evaluating the AskMe retrievalengine using the BEIR benchmark datasets.
Towards Standardization of Web Service Protocols for NLPaaS
Several web services for various natural language processing (NLP) tasks ({`}{`}NLP-as-a-service{''} or NLPaaS) have recently been made publicly available.
Interchange Formats for Visualization: LIF and MMIF
Promoting interoperrable computational linguistics (CL) and natural language processing (NLP) application platforms and interchange-able data formats have contributed improving discoverabilty and accessbility of the openly available NLP software.
Infrastructure for Semantic Annotation in the Genomics Domain
The corpus database is distributed to permit fast indexing, and provides a simple web front-end with corpus linguistics methods for sub-corpus comparison and retrieval.
A Multi-Platform Annotation Ecosystem for Domain Adaptation
This paper describes an ecosystem consisting of three independent text annotation platforms.
Representation and Interchange of Linguistic Annotation. An In-Depth, Side-by-Side Comparison of Three Designs
We expect that a more in-depth understanding of these choices across designs may led to increased harmonization, or at least to more informed design of future representations.
LAPPS/Galaxy: Current State and Next Steps
The US National Science Foundation (NSF) SI2-funded LAPPS/Galaxy project has developed an open-source platform for enabling complex analyses while hiding complexities associated with underlying infrastructure, that can be accessed through a web interface, deployed on any Unix system, or run from the cloud.
The Language Application Grid and Galaxy
The NSF-SI2-funded LAPPS Grid project is a collaborative effort among Brandeis University, Vassar College, Carnegie-Mellon University (CMU), and the Linguistic Data Consortium (LDC), which has developed an open, web-based infrastructure through which resources can be easily accessed and within which tailored language services can be efficiently composed, evaluated, disseminated and consumed by researchers, developers, and students across a wide variety of disciplines.
The Language Application Grid
The Language Application (LAPPS) Grid project is establishing a framework that enables language service discovery, composition, and reuse and promotes sustainability, manageability, usability, and interoperability of natural language Processing (NLP) components.
Empirical Comparisons of MASC Word Sense Annotations
We analyze how different conceptions of lexical semantics affect sense annotations and how multiple sense inventories can be compared empirically, based on annotated text.
The MASC Word Sense Corpus
The MASC project has produced a multi-genre corpus with multiple layers of linguistic annotation, together with a sentence corpus containing WordNet 3. 1 sense tags for 1000 occurrences of each of 100 words produced by multiple annotators, accompanied by indepth inter-annotator agreement data.
