74 citations · 161 across the 19 of their papers we have counts for
19 papers
User-Aware Multilingual Abusive Content Detection in Social Media
Mohammad Zia Ur Rehman, Somya Mehta, Kuldeep Singh +2
Despite growing efforts to halt distasteful content on social media, multilingualism has added a new dimension to this problem. The scarcity of resources makes the challenge even g…
Contrastive Representation Learning for Conversational Question Answering over Knowledge Graphs
Endri Kacupaj, Kuldeep Singh, Maria Maleshkova +1
This paper addresses the task of conversational question answering (ConvQA) over knowledge graphs (KGs). The majority of existing ConvQA methods rely on full supervision signals wi…
An Answer Verbalization Dataset for Conversational Question Answerings over Knowledge Graphs
Endri Kacupaj, Kuldeep Singh, Maria Maleshkova +1
We introduce a new dataset for conversational question answering over Knowledge Graphs (KGs) with verbalized answers. Question answering over KGs is currently focused on answer gen…
Plumber: A Modular Framework to Create Information Extraction Pipelines
Mohamad Yaser Jaradeh, Kuldeep Singh, Markus Stocker +1
Information Extraction (IE) tasks are commonly studied topics in various domains of research. Hence, the community continuously produces multiple techniques, solutions, and tools t…
Triple Classification for Scholarly Knowledge Graph Completion
Mohamad Yaser Jaradeh, Kuldeep Singh, Markus Stocker +1
Scholarly Knowledge Graphs (KGs) provide a rich source of structured information representing knowledge encoded in scientific publications. With the sheer volume of published scien…
KGPool: Dynamic Knowledge Graph Context Selection for Relation Extraction
Abhishek Nadgeri, Anson Bastos, Kuldeep Singh +4
We present a novel method for relation extraction (RE) from a single sentence, mapping the sentence and two given entities to a canonical fact in a knowledge graph (KG). Especially…
Conversational Question Answering over Knowledge Graphs with Transformer and Graph Attention Networks
Endri Kacupaj, Joan Plepi, Kuldeep Singh +3
This paper addresses the task of (complex) conversational question answering over a knowledge graph. For this task, we propose LASAGNE (muLti-task semAntic parSing with trAnsformer…
ParaQA: A Question Answering Dataset with Paraphrase Responses for Single-Turn Conversation
Endri Kacupaj, Barshana Banerjee, Kuldeep Singh +1
This paper presents ParaQA, a question answering (QA) dataset with multiple paraphrased responses for single-turn conversation over knowledge graphs (KG). The dataset was created u…
Context Transformer with Stacked Pointer Networks for Conversational Question Answering over Knowledge Graphs
Joan Plepi, Endri Kacupaj, Kuldeep Singh +2
Neural semantic parsing approaches have been widely used for Question Answering (QA) systems over knowledge graphs. Such methods provide the flexibility to handle QA datasets with…
Better Call the Plumber: Orchestrating Dynamic Information Extraction Pipelines
Mohamad Yaser Jaradeh, Kuldeep Singh, Markus Stocker +2
In the last decade, a large number of Knowledge Graph (KG) information extraction approaches were proposed. Albeit effective, these efforts are disjoint, and their collective stren…
CHOLAN: A Modular Approach for Neural Entity Linking on Wikipedia and Wikidata
Manoj Prabhakar Kannan Ravi, Kuldeep Singh, Isaiah Onando Mulang' +3
In this paper, we propose CHOLAN, a modular approach to target end-to-end entity linking (EL) over knowledge bases. CHOLAN consists of a pipeline of two transformer-based models in…
RECON: Relation Extraction using Knowledge Graph Context in a Graph Neural Network
Anson Bastos, Abhishek Nadgeri, Kuldeep Singh +4
In this paper, we present a novel method named RECON, that automatically identifies relations in a sentence (sentential relation extraction) and aligns to a knowledge graph (KG). R…
Evaluating the Impact of Knowledge Graph Context on Entity Disambiguation Models
Isaiah Onando Mulang', Kuldeep Singh, Chaitali Prabhu +3
Pretrained Transformer models have emerged as state-of-the-art approaches that learn contextual information from text to improve the performance of several NLP tasks. These models,…
Template-Based Question Answering over Linked Geospatial Data
Dharmen Punjani, Markos Iliakis, Theodoros Stefou +13
Large amounts of geospatial data have been made available recently on the linked open data cloud and the portals of many national cartographic agencies (e.g., OpenStreetMap data, a…
Falcon 2.0: An Entity and Relation Linking Tool over Wikidata
Ahmad Sakor, Kuldeep Singh, Anery Patel +1
The Natural Language Processing (NLP) community has significantly contributed to the solutions for entity and relation recognition from the text, and possibly linking them to prope…
Encoding Knowledge Graph Entity Aliases in Attentive Neural Network for Wikidata Entity Linking
Isaiah Onando Mulang, Kuldeep Singh, Akhilesh Vyas +4
The collaborative knowledge graphs such as Wikidata excessively rely on the crowd to author the information. Since the crowd is not bound to a standard protocol for assigning entit…
Towards Optimisation of Collaborative Question Answering over Knowledge Graphs
Kuldeep Singh, Mohamad Yaser Jaradeh, Saeedeh Shekarpour +5
Collaborative Question Answering (CQA) frameworks for knowledge graphs aim at integrating existing question answering (QA) components for implementing sequences of QA tasks (i.e. Q…
No One is Perfect: Analysing the Performance of Question Answering Components over the DBpedia Knowledge Graph
Kuldeep Singh, Ioanna Lytra, Arun Sethupat Radhakrishna +3
Question answering (QA) over knowledge graphs has gained significant momentum over the past five years due to the increasing availability of large knowledge graphs and the rising i…
Question Answering on Linked Data: Challenges and Future Directions
Saeedeh Shekarpour, Denis Lukovnikov, Ashwini Jaya Kumar +4
Question Answering (QA) systems are becoming the inspiring model for the future of search engines. While recently, underlying datasets for QA systems have been promoted from unstru…