1 code implementation • 12 Aug 2021 • Anson Bastos, Kuldeep Singh, Abhishek Nadgeri, Saeedeh Shekarpour, Isaiah Onando Mulang, Johannes Hoffart
A few KGE techniques address interpretability, i. e., mapping the connectivity patterns of the relations (i. e., symmetric/asymmetric, inverse, and composition) to a geometric interpretation such as rotations.
1 code implementation • Findings (ACL) 2021 • Abhishek Nadgeri, Anson Bastos, Kuldeep Singh, Isaiah Onando Mulang', Johannes Hoffart, Saeedeh Shekarpour, Vijay Saraswat
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).
1 code implementation • 17 Mar 2021 • Sunday C. Ngwobia, Saeedeh Shekarpour, Faisal Alshargi
The current encyclopedias are limited to highly popular entities, which are far fewer compared with the emerging entities.
1 code implementation • EACL 2021 • Manoj Prabhakar Kannan Ravi, Kuldeep Singh, Isaiah Onando Mulang', Saeedeh Shekarpour, Johannes Hoffart, Jens Lehmann
Our empirical study was conducted on two well-known knowledge bases (i. e., Wikidata and Wikipedia).
Ranked #1 on Entity Linking on MSNBC
no code implementations • EMNLP (intexsempar) 2020 • Saeedeh Shekarpour, Abhishek Nadgeri, Kuldeep Singh
In the era of Big Knowledge Graphs, Question Answering (QA) systems have reached a milestone in their performance and feasibility.
1 code implementation • 18 Sep 2020 • Anson Bastos, Abhishek Nadgeri, Kuldeep Singh, Isaiah Onando Mulang', Saeedeh Shekarpour, Johannes Hoffart, Manohar Kaul
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).
no code implementations • 12 Dec 2019 • Isaiah Onando Mulang, Kuldeep Singh, Akhilesh Vyas, Saeedeh Shekarpour, Maria Esther Vidal, Jens Lehmann, Soren Auer
In this paper, we examine the role of knowledge graph context on an attentive neural network approach for entity linking on Wikidata.
no code implementations • 14 Aug 2019 • Kuldeep Singh, Mohamad Yaser Jaradeh, Saeedeh Shekarpour, Akash Kulkarni, Arun Sethupat Radhakrishna, Ioanna Lytra, Maria-Esther Vidal, Jens Lehmann
Collaborative Question Answering (CQA) frameworks for knowledge graphs aim at integrating existing question answering (QA) components for implementing sequences of QA tasks (i. e. QA pipelines).
no code implementations • 4 Jul 2019 • Saeedeh Shekarpour, Faisal Al-Shargi
The increasing rate of information pollution on the Web requires novel solutions to tackle that.
1 code implementation • NAACL 2019 • Ahmad Sakor, on, Isaiah o Mulang{'}, Kuldeep Singh, Saeedeh Shekarpour, Maria Esther Vidal, Jens Lehmann, S{\"o}ren Auer
Short texts challenge NLP tasks such as named entity recognition, disambiguation, linking and relation inference because they do not provide sufficient context or are partially malformed (e. g. wrt.
1 code implementation • 24 Nov 2018 • Somayeh Asadifar, Mohsen Kahani, Saeedeh Shekarpour
Exploiting the answer to complex questions is further challenged if it requires integrating knowledge from unstructured data sources, i. e., textual corpus, as well as structured data sources, i. e., knowledge graphs.
no code implementations • 1 Nov 2018 • Mohammadreza Rezvan, Saeedeh Shekarpour, Faisal Alshargi, Krishnaprasad Thirunarayan, Valerie L. Shalin, Amit Sheth
In this paper, we introduce the notion of contextual type to harassment involving five categories: (i) sexual, (ii) racial, (iii) appearance-related, (iv) intellectual and (v) political.
3 code implementations • 26 Sep 2018 • Kuldeep Singh, Ioanna Lytra, Arun Sethupat Radhakrishna, Saeedeh Shekarpour, Maria-Esther Vidal, Jens Lehmann
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 importance of question answering for user interaction.
no code implementations • 6 Aug 2018 • Saeedeh Shekarpour, Ankita Saxena, Krishnaprasad Thirunarayan, Valerie L. Shalin, Amit Sheth
The ever-growing datasets published on Linked Open Data mainly contain encyclopedic information.
1 code implementation • 12 Mar 2018 • Faisal Alshargi, Saeedeh Shekarpour, Tommaso Soru, Amit Sheth
This deficiency is further sensed with respect to embeddings generated for structured data because there are no concrete evaluation metrics measuring the quality of the encoded structure as well as semantic patterns in the embedding space.
no code implementations • 26 Feb 2018 • Mohammadreza Rezvan, Saeedeh Shekarpour, Lakshika Balasuriya, Krishnaprasad Thirunarayan, Valerie Shalin, Amit Sheth
In this paper, we publish first, a quality annotated corpus and second, an offensive words lexicon capturing different types type of harassment as (i) sexual harassment, (ii) racial harassment, (iii) appearance-related harassment, (iv) intellectual harassment, and (v) political harassment. We crawled data from Twitter using our offensive lexicon.
no code implementations • 19 Jan 2017 • Saeedeh Shekarpour, Faisal Al-Shargi, Valerie Shalin, Krishnaprasad Thirunarayan, Amit P. Sheth
These use-cases demonstrate the benefits of using CEVO for annotation: (i) annotating English verbs from an abstract conceptualization, (ii) playing the role of an upper ontology for organizing ontological properties, and (iii) facilitating the annotation of text relations using any underlying vocabulary.