Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Introduction to the Special Issue on Cross-Language Algorithms and Applications
Authors: Marta R. Costa-jussà, Srinivas Bangalore, Patrik Lambert, Lluís Màrquez, Elena Montiel-Ponsoda
JAIR 2016 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this introduction, we provide the reader with the motivation for this special issue and summarize the contributions of the papers that have been included. |
| Researcher Affiliation | Collaboration | Marta R. Costa-juss a TALP Research Center Universitat Polit ecnica de Catalunya... Srinivas Bangalore EMAIL Interactions Labs... Patrik Lambert EMAIL Computational Linguistics Group Universitat Pompeu Fabra... Llu ıs M arquez EMAIL Qatar Computing Research Institute... Elena Montiel-Ponsoda EMAIL Ontology Engineering Group Universidad Polit ecnica de Madrid |
| Pseudocode | No | The paper provides an introduction and summary of research in cross-language algorithms and applications, but it does not contain any pseudocode or algorithm blocks. |
| Open Source Code | No | This paper is an introduction to a special issue and summarizes contributions from other papers. It does not present original methodology with corresponding source code. |
| Open Datasets | Yes | Annotation efforts have been undertaken and invaluable resources of varying amounts of texts have been created during the past decades for certain languages, for example, Penn Treebank (Marcus, Marcinkiewicz, & Santorini, 1993), French Treebank (Abeill e, 2003), NEGRA Treebank (Skut, Brants, & Uszkoreit, 1998), Prague Dependency Treebank (Hajiˇc, B ohmov a, Hajiˇcov a, & Vidov a-Hladk a, 2000). ... This paper evaluates a machine translation service, Google Translate7, and a multilingual encyclopedic dictionary and semantic network, Babel Net8, for correctness and coverage of the suggested translations and mapping selection capabilities (word-disambiguation). |
| Dataset Splits | No | This paper serves as an introduction to a special issue and summarizes other research. It does not describe original experiments with specific dataset splits. |
| Hardware Specification | No | This paper is an introduction to a special issue and does not report on specific experimental hardware used. |
| Software Dependencies | No | This paper is an introduction to a special issue and does not specify software dependencies or versions for its own methodology. |
| Experiment Setup | No | As an introductory paper summarizing other research, this document does not detail specific experimental setup parameters or hyperparameters. |