ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis

We introduce ArVoice, a multi-speaker Modern Standard Arabic (MSA) speech corpus with diacritized transcriptions, intended for multi-speaker speech synthesis, and can be useful for other tasks such as speech-based diacritic restoration, voice conversion, and deepfake detection. ArVoice comprises: (1) a new professionally recorded set from six voice talents with diverse demographics, (2) a modified subset of the Arabic Speech Corpus; and (3) high-quality synthetic speech from two commercial systems. The complete corpus consists of a total of 83.52 hours of speech across 11 voices; around 10 hours consist of human voices from 7 speakers. We train three open-source TTS and two voice conversion systems to illustrate the use cases of the dataset. The corpus is available for research use.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: ArVoice: A Multi-Speaker Dataset for Arabic Speech Synthesis
Abstract: We introduce ArVoice, a multi-speaker Modern Standard Arabic (MSA) speech corpus with diacritized transcriptions, intended for multi-speaker speech synthesis, and can be useful for other tasks such as speech-based diacritic restoration, voice conversion, and deepfake detection. ArVoice comprises: (1) a new professionally recorded set from six voice talents with diverse demographics, (2) a modified subset of the Arabic Speech Corpus; and (3) high-quality synthetic speech from two commercial systems. The complete corpus consists of a total of 83.52 hours of speech across 11 voices; around 10 hours consist of human voices from 7 speakers. We train three open-source TTS and two voice conversion systems to illustrate the use cases of the dataset. The corpus is available for research use.

[Assistant] Dataset


A Tutorial for Evaluating Cure Model Appropriateness

In survival analysis, traditional models assume all individuals will eventually experience the event of interest. However, advances in therapeutics have led to multiple clinical contexts with potentially curative therapies, and in these contexts, certain individuals may never experience the event. Statisticians have developed cure models as a methodology to address this challenge. Nonetheless, despite significant statistical advances in cure models, we have seen more limited uptake in biomedical applications, and we hypothesize that this is caused by limited guidance in the appropriate application of cure models. Cure models require specific identifiability conditions for valid parameter estimation, and previous reports have demonstrated significant issues with the inappropriate application of cure models. Existing tutorials for cure models focus on model implementation and either assume or provide only limited guidance on whether cure modeling is appropriate for the given dataset. This tutorial addresses this gap by describing a systematic procedure that integrates clinical judgment, visual inspection of Kaplan-Meier curves, and quantitative evaluation. We provide a worked example using data from a randomized clinical trial in acute myeloid leukemia, and we also summarize findings from a series of other datasets of hematopoietic cell transplantation to suggest broad practical guidance for choosing to apply cure models. By systematically evaluating cure model appropriateness before fitting these models, researchers can achieve more reliable survival analysis and improved clinical decision-making.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: A Tutorial for Evaluating Cure Model Appropriateness
Abstract: In survival analysis, traditional models assume all individuals will eventually experience the event of interest. However, advances in therapeutics have led to multiple clinical contexts with potentially curative therapies, and in these contexts, certain individuals may never experience the event. Statisticians have developed cure models as a methodology to address this challenge. Nonetheless, despite significant statistical advances in cure models, we have seen more limited uptake in biomedical applications, and we hypothesize that this is caused by limited guidance in the appropriate application of cure models. Cure models require specific identifiability conditions for valid parameter estimation, and previous reports have demonstrated significant issues with the inappropriate application of cure models. Existing tutorials for cure models focus on model implementation and either assume or provide only limited guidance on whether cure modeling is appropriate for the given dataset. This tutorial addresses this gap by describing a systematic procedure that integrates clinical judgment, visual inspection of Kaplan-Meier curves, and quantitative evaluation. We provide a worked example using data from a randomized clinical trial in acute myeloid leukemia, and we also summarize findings from a series of other datasets of hematopoietic cell transplantation to suggest broad practical guidance for choosing to apply cure models. By systematically evaluating cure model appropriateness before fitting these models, researchers can achieve more reliable survival analysis and improved clinical decision-making.

[Assistant] Methodology


SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting

Neural population models, which predict the joint firing of many simultaneously recorded neurons forward in time, are typically evaluated by a single aggregate Pearson correlation $r$ between predicted and actual spike counts, a number that masks critical structure. We argue that how we evaluate spike forecasting matters as much as what we build, and introduce SpikeProphecy, the first large-scale benchmark for causal, autoregressive spike-count forecasting on real electrophysiology recordings. Our core contribution is a population metric decomposition that separates aggregate performance into temporal fidelity, spatial pattern accuracy, and magnitude-invariant alignment. The decomposition surfaces aspects of the underlying data that an aggregate scalar collapses together. We apply the protocol to 105 Neuropixels sessions (Steinmetz 2019 + IBL Repeated Site; ~89,800 neurons) with seven architecture baselines spanning four structural families: four SSMs (three diagonal and one non-diagonal), a Transformer, an LSTM, and a spiking network. The decomposition surfaces a brain-region predictability ranking that reproduces across all seven baselines and survives ANCOVA correction for firing-statistics constraints (region $ΔR^2 = 0.018$ above the firing-statistics covariates). It also exposes a sub-Poisson evaluation floor where rigorous metrics combine with genuine biophysical constraints on regular spike trains, and yields a negative result on KL-on-output-rates distillation for ANN-to-SNN transfer in this Poisson count domain.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: SpikeProphecy: A Large-Scale Benchmark for Autoregressive Neural Population Forecasting
Abstract: Neural population models, which predict the joint firing of many simultaneously recorded neurons forward in time, are typically evaluated by a single aggregate Pearson correlation $r$ between predicted and actual spike counts, a number that masks critical structure. We argue that how we evaluate spike forecasting matters as much as what we build, and introduce SpikeProphecy, the first large-scale benchmark for causal, autoregressive spike-count forecasting on real electrophysiology recordings. Our core contribution is a population metric decomposition that separates aggregate performance into temporal fidelity, spatial pattern accuracy, and magnitude-invariant alignment. The decomposition surfaces aspects of the underlying data that an aggregate scalar collapses together. We apply the protocol to 105 Neuropixels sessions (Steinmetz 2019 + IBL Repeated Site; ~89,800 neurons) with seven architecture baselines spanning four structural families: four SSMs (three diagonal and one non-diagonal), a Transformer, an LSTM, and a spiking network. The decomposition surfaces a brain-region predictability ranking that reproduces across all seven baselines and survives ANCOVA correction for firing-statistics constraints (region $ΔR^2 = 0.018$ above the firing-statistics covariates). It also exposes a sub-Poisson evaluation floor where rigorous metrics combine with genuine biophysical constraints on regular spike trains, and yields a negative result on KL-on-output-rates distillation for ANN-to-SNN transfer in this Poisson count domain.

[Assistant] Dataset


Properties of the thinnest cold HI clouds in the diffuse interstellar medium

We have obtained deep HI observations in the direction of 22 continuum sources without previously detected cold neutral medium (CNM). 18 CNM clouds were detected with the typical HI column density of $3\times10^{18}$ cm$^{-2}$. Our surprisingly high detection rate suggests that clouds with low HI column densities are quite common in the interstellar medium. These clouds appear to represent an extension of the traditional CNM cloud population, yet have sizes in hundreds to thousands of AUs. We present properties of the newly-detected CNM sample, and discuss several theoretical avenues important for understanding the production mechanisms of these clouds.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Properties of the thinnest cold HI clouds in the diffuse interstellar medium
Abstract: We have obtained deep HI observations in the direction of 22 continuum sources without previously detected cold neutral medium (CNM). 18 CNM clouds were detected with the typical HI column density of $3\times10^{18}$ cm$^{-2}$. Our surprisingly high detection rate suggests that clouds with low HI column densities are quite common in the interstellar medium. These clouds appear to represent an extension of the traditional CNM cloud population, yet have sizes in hundreds to thousands of AUs. We present properties of the newly-detected CNM sample, and discuss several theoretical avenues important for understanding the production mechanisms of these clouds.

[Assistant]
high confidence

Dataset

Explanation: high confidence


Parallel Guided Local Search and Some Preliminary Experimental Results for Continuous Optimization

This paper proposes a Parallel Guided Local Search (PGLS) framework for continuous optimization. In PGLS, several guided local search (GLS) procedures (agents) are run for solving the optimization problem. The agents exchange information for speeding up the search. For example, the information exchanged could be knowledge about the landscape obtained by the agents. The proposed algorithm is applied to continuous optimization problems. The preliminary experimental results show that the algorithm is very promising .

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Parallel Guided Local Search and Some Preliminary Experimental Results for Continuous Optimization
Abstract: This paper proposes a Parallel Guided Local Search (PGLS) framework for continuous optimization. In PGLS, several guided local search (GLS) procedures (agents) are run for solving the optimization problem. The agents exchange information for speeding up the search. For example, the information exchanged could be knowledge about the landscape obtained by the agents. The proposed algorithm is applied to continuous optimization problems. The preliminary experimental results show that the algorithm is very promising .

[Assistant] Methodology


The CORA dataset: validation and diagnostics of ocean temperature and  salinity in situ measurements

Abstract. The French program Coriolis as part of the French oceanographic operational system produces the COriolis dataset for Re-Analysis (CORA) on a yearly basis which is based on temperature and salinity measurements on observed levels from different data types. The latest release of CORA covers the period 1990 to 2010. To qualify this dataset, several tests have been developed to improve in a homogeneous way the quality of the raw dataset and to fit the level required by the physical ocean re-analysis activities (assimilation and validation). These include some simple tests, climatological tests and a model background check based on a global ocean reanalysis. Visual quality control (QC) is performed on all suspicious temperature (T) and salinity (S) profiles identified by the tests and quality flags are modified in the dataset if necessary. In addition, improved diagnostic tools were developed – including global ocean indicators – which give information on the potential and quality of the CORA dataset for all applications. This Coriolis product is available on request through the MyOcean Service Desk (http://www.myocean.eu/).

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: The CORA dataset: validation and diagnostics of ocean temperature and  salinity in situ measurements
Abstract: Abstract. The French program Coriolis as part of the French oceanographic operational system produces the COriolis dataset for Re-Analysis (CORA) on a yearly basis which is based on temperature and salinity measurements on observed levels from different data types. The latest release of CORA covers the period 1990 to 2010. To qualify this dataset, several tests have been developed to improve in a homogeneous way the quality of the raw dataset and to fit the level required by the physical ocean re-analysis activities (assimilation and validation). These include some simple tests, climatological tests and a model background check based on a global ocean reanalysis. Visual quality control (QC) is performed on all suspicious temperature (T) and salinity (S) profiles identified by the tests and quality flags are modified in the dataset if necessary. In addition, improved diagnostic tools were developed – including global ocean indicators – which give information on the potential and quality of the CORA dataset for all applications. This Coriolis product is available on request through the MyOcean Service Desk (http://www.myocean.eu/).

[Assistant] Dataset


Optimizing service mesh performance and security trade-offs in Kubernetes with Istio and Linkerd

Service mesh technologies have emerged as critical components in Kubernetes environments, offering essential capabilities for managing and securing microservice communication. This article presents an empirical comparison between Istio and Linkerd, examining their architectural differences and performance characteristics under various security configurations. The investigation establishes baseline metrics for each service meshes and measures the impact of progressively enabling security features including mutual TLS encryption and authorization policies. Through controlled laboratory testing and production environment data, the comparison reveals distinct trade-offs between security posture and performance overhead. Istio provides comprehensive security features at the cost of increased resource consumption, while Linkerd delivers efficient performance with a more streamlined security model. The article offers optimization strategies for enterprise deployments, including configuration techniques for balancing security and performance, scaling considerations for large environments, and workload-specific tuning recommendations. A decision framework guides implementation choices based on specific security requirements, ultimately providing architects and DevOps professionals with actionable insights for maximizing both security and performance in Kubernetes service mesh deployments.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Optimizing service mesh performance and security trade-offs in Kubernetes with Istio and Linkerd
Abstract: Service mesh technologies have emerged as critical components in Kubernetes environments, offering essential capabilities for managing and securing microservice communication. This article presents an empirical comparison between Istio and Linkerd, examining their architectural differences and performance characteristics under various security configurations. The investigation establishes baseline metrics for each service meshes and measures the impact of progressively enabling security features including mutual TLS encryption and authorization policies. Through controlled laboratory testing and production environment data, the comparison reveals distinct trade-offs between security posture and performance overhead. Istio provides comprehensive security features at the cost of increased resource consumption, while Linkerd delivers efficient performance with a more streamlined security model. The article offers optimization strategies for enterprise deployments, including configuration techniques for balancing security and performance, scaling considerations for large environments, and workload-specific tuning recommendations. A decision framework guides implementation choices based on specific security requirements, ultimately providing architects and DevOps professionals with actionable insights for maximizing both security and performance in Kubernetes service mesh deployments.

[Assistant] Applied


This book guides the drafting of patent applications from a practical perspective an gives all knowhow required to with a patent. Intended as an introductory text, it covers the entire process of drafting of a patent application and includes many helpful examples or case studies, illustrating the process from start to finish. This book also includes papers on working of patents in India which will give an idea to patentee to how to keep his patent alive. Looking to the increasing awareness among the inventors, investors and scientists and the increasing cost of patent attorneys, editors tried to publish a book containing papers from patent attorneys, scientists and innovators with practical case studies.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Irrigation and Agricultural Drainage Engineering
Abstract: This book guides the drafting of patent applications from a practical perspective an gives all knowhow required to with a patent. Intended as an introductory text, it covers the entire process of drafting of a patent application and includes many helpful examples or case studies, illustrating the process from start to finish. This book also includes papers on working of patents in India which will give an idea to patentee to how to keep his patent alive. Looking to the increasing awareness among the inventors, investors and scientists and the increasing cost of patent attorneys, editors tried to publish a book containing papers from patent attorneys, scientists and innovators with practical case studies.

[Assistant]
The title and DOI identify “Irrigation and Agricultural Drainage Engineering,” but the displayed abstract discusses patent application drafting and patent practice. The abstract appears mismatched with the identified publication, making reliable intent classification difficult.

Review

Explanation: The title and DOI identify “Irrigation and Agricultural Drainage Engineering,” but the displayed abstract discusses patent application drafting and patent practice. The abstract appears mismatched with the identified publication, making reliable intent classification difficult.


A Review of the Strategies for Promoting Sustainable Agricultural Production and Family Food Security in Nigeria

The need to provide unrestricted access to quality food and ensure nutrition security for all citizens has been at the forefront of the development agenda of all countries across the globe. Considering the cardinal role of agriculture in ensuring sustainable family food and nutrition security, goal number two of the United Nations Sustainable Development Goals (SDGs) is focused on the need to “End hunger, achieve food security and improved nutrition, and promote sustainable agriculture production”. This paper reviewed the strategies for promoting sustainable agricultural production and family food security in Nigeria. A literature search was conducted through databases such as Scopus, ISI Web of Knowledge, google scholar, directory of open access journal (DOAJ), and research gate. The search terms included keywords such as food security, strategies for promoting food security, sustainable agricultural production, family food security, sustainable production, and Nigeria among others. A total of 108 results were returned from the search, 72 papers were relevant to the study, while the authors were unable to access 11 of the papers. The authors assessed the full texts of all the available articles through narrative synthesis following laid down eligibility criteria. The results revealed that several studies have been conducted on the strategies for promoting sustainable agricultural production and family food security in Nigeria. Several recommendations were made among which is the need to repurpose agricultural development policies, empower small-scale farmers, adopt sustainable agricultural practices, promote all-season agricultural production, and provide modern agricultural food processing and storage facilities.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: A Review of the Strategies for Promoting Sustainable Agricultural Production and Family Food Security in Nigeria
Abstract: The need to provide unrestricted access to quality food and ensure nutrition security for all citizens has been at the forefront of the development agenda of all countries across the globe. Considering the cardinal role of agriculture in ensuring sustainable family food and nutrition security, goal number two of the United Nations Sustainable Development Goals (SDGs) is focused on the need to “End hunger, achieve food security and improved nutrition, and promote sustainable agriculture production”. This paper reviewed the strategies for promoting sustainable agricultural production and family food security in Nigeria. A literature search was conducted through databases such as Scopus, ISI Web of Knowledge, google scholar, directory of open access journal (DOAJ), and research gate. The search terms included keywords such as food security, strategies for promoting food security, sustainable agricultural production, family food security, sustainable production, and Nigeria among others. A total of 108 results were returned from the search, 72 papers were relevant to the study, while the authors were unable to access 11 of the papers. The authors assessed the full texts of all the available articles through narrative synthesis following laid down eligibility criteria. The results revealed that several studies have been conducted on the strategies for promoting sustainable agricultural production and family food security in Nigeria. Several recommendations were made among which is the need to repurpose agricultural development policies, empower small-scale farmers, adopt sustainable agricultural practices, promote all-season agricultural production, and provide modern agricultural food processing and storage facilities.

[Assistant] Review


Diagnostic Accuracy of a Large Language Model in Pediatric Case Studies

This diagnostic study evaluates the accuracy of a large language model against physician diagnoses in pediatric cases.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Diagnostic Accuracy of a Large Language Model in Pediatric Case Studies
Abstract: This diagnostic study evaluates the accuracy of a large language model against physician diagnoses in pediatric cases.

[Assistant] Applied


Pretraining Beats Architecture Benchmark Limits and the Role of Recurrent Depth Transformers in Constrained Molecular Generation

This manuscript presents a controlled benchmark study evaluating recurrent-depth transformers against pretrained language models for constrained molecular generation. Using easy, medium, and hard benchmark settings, the study demonstrates that benchmark difficulty strongly influences conclusions about architectural performance, with pretrained models outperforming architecture-first training under stringent constraints. The findings highlight the importance of robust benchmark design for evaluating AI models in molecular discovery and provide recommendations for future benchmark development. Experimental evaluations are conducted on publicly available molecular datasets, with an emphasis on reproducibility and transparent benchmark methodology.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Pretraining Beats Architecture Benchmark Limits and the Role of Recurrent Depth Transformers in Constrained Molecular Generation
Abstract: This manuscript presents a controlled benchmark study evaluating recurrent-depth transformers against pretrained language models for constrained molecular generation. Using easy, medium, and hard benchmark settings, the study demonstrates that benchmark difficulty strongly influences conclusions about architectural performance, with pretrained models outperforming architecture-first training under stringent constraints. The findings highlight the importance of robust benchmark design for evaluating AI models in molecular discovery and provide recommendations for future benchmark development. Experimental evaluations are conducted on publicly available molecular datasets, with an emphasis on reproducibility and transparent benchmark methodology.

[Assistant] Dataset


[Experimental studies on the optimal therapeutic mode of intra-arterial infusion of 5-fluorouracil. (1) Preparation of an animal model for continuous intra-arterial infusion and comparison of the therapeutic and adverse effects of 5-fluorouracil delivered by various modes].

5-Fluorouracil (5-FU) is one of the most popular anticancer drugs, especially in treatment of for adenocarcinoma; however, an optimal therapeutic schedule of 5-FU is not determined even now. An animal model for continuous intraarterial infusion in rats was constructed using retrograde cannulation to aorta via right femoral artery in order to study the intraarterial and systemic effects of 5-FU on Yoshida sarcoma implanted in left fore limb and hind limb subcutaneously. By implanting Yoshida sarcoma in fore and hind limb and cannulating and infusing aorta, the regional and systemic antitumor effects could be compared in the same animal. Antitumor effect and toxicity after intraarterial 5-FU administration was studied at various infusion time and doses. The results revealed that intraarterial infusion of 5-FU was more effective than its systemic administration from view points of the antitumor effect. The antitumor effect after one shot intraarterial injection of 5-FU was ar superior to that after continuous infusion of 5-FU. However, toxicity after one shot injection was much more severe than continuous infusion. Consequently, the desirable administration schedule of 5-FU appears to be an intraarterial infusion as short time as possible within tolerable toxicity.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: [Experimental studies on the optimal therapeutic mode of intra-arterial infusion of 5-fluorouracil. (1) Preparation of an animal model for continuous intra-arterial infusion and comparison of the therapeutic and adverse effects of 5-fluorouracil delivered by various modes].
Abstract: 5-Fluorouracil (5-FU) is one of the most popular anticancer drugs, especially in treatment of for adenocarcinoma; however, an optimal therapeutic schedule of 5-FU is not determined even now. An animal model for continuous intraarterial infusion in rats was constructed using retrograde cannulation to aorta via right femoral artery in order to study the intraarterial and systemic effects of 5-FU on Yoshida sarcoma implanted in left fore limb and hind limb subcutaneously. By implanting Yoshida sarcoma in fore and hind limb and cannulating and infusing aorta, the regional and systemic antitumor effects could be compared in the same animal. Antitumor effect and toxicity after intraarterial 5-FU administration was studied at various infusion time and doses. The results revealed that intraarterial infusion of 5-FU was more effective than its systemic administration from view points of the antitumor effect. The antitumor effect after one shot intraarterial injection of 5-FU was ar superior to that after continuous infusion of 5-FU. However, toxicity after one shot injection was much more severe than continuous infusion. Consequently, the desirable administration schedule of 5-FU appears to be an intraarterial infusion as short time as possible within tolerable toxicity.

[Assistant]
The study primarily applies an experimental animal model to evaluate different intra-arterial administration schedules of 5-fluorouracil, comparing antitumor effects and toxicity to determine a desirable therapeutic schedule. The animal model and experimental methodology serve the practical therapeutic objective.

Applied

Explanation: The study primarily applies an experimental animal model to evaluate different intra-arterial administration schedules of 5-fluorouracil, comparing antitumor effects and toxicity to determine a desirable therapeutic schedule. The animal model and experimental methodology serve the practical therapeutic objective.


Natural language processing: a prolog perspective

Natural language processing (NLP) is a vibrant field of interdisciplinary Computer Science research. Ultimately, NLP seeks to build intelligence into software so that software will be able to process a natural language as skillfully and artfully as humans. Prolog, a general purpose logic programming language, has been used extensively to develop NLP applications or components thereof. This report is concerned with introducing the interested reader to the broad field of NLP with respect to NLP applications that are built in Prolog or from Prolog components.

[System] You are a multilingual research paper intent classifier. Given a paper title and abstract, classify its primary research intent as exactly one of: Methodology, Dataset, Review, Applied, Theoretical, Unclassifiable.

[User]
Classify the research intent of this paper:

Title: Natural language processing: a prolog perspective
Abstract: Natural language processing (NLP) is a vibrant field of interdisciplinary Computer Science research. Ultimately, NLP seeks to build intelligence into software so that software will be able to process a natural language as skillfully and artfully as humans. Prolog, a general purpose logic programming language, has been used extensively to develop NLP applications or components thereof. This report is concerned with introducing the interested reader to the broad field of NLP with respect to NLP applications that are built in Prolog or from Prolog components.

[Assistant] Methodology