Pinaki Bhaskar

Learn More
The article presents the experiments carried out as part of the participation in the pilot task of QA4MRE@CLEF 2013. In the developed system, we have first generated answer pattern by combining the question and each answer option to form the Hypothesis (H). Stop words and interrogative word are removed from each H and query words are identified to retrieve(More)
This paper reports about our work in the ICON 2009 NLP TOOLS CONTEST: Parsing. We submitted two runs for Bengali. A statistical CRF based model followed by a rule-based post-processing technique has been used. The system has been trained on the NLP TOOLS CONTEST: ICON 2009 datasets. The system demonstrated an unlabeled attachment score (UAS) of 74.09%,(More)
The article presents the experiments carried out as part of the participation in the main task of QA4MRE@CLEF 2011. We have submitted total five unique runs in the main task: two runs from systems based on Answer Validation (AV) machine reading techniques, one run from systems based on Question Answering (QA) techniques while the last two runs are hybrid(More)
The article presents the experiments carried out as part of the participation in the main task of QA4MRE@CLEF 2012. In the developed system, we first combine the question and each answer option to form the Hypothesis (H). Stop words are removed from each H and query words are identified to retrieve the most relevant sentences from the associated document(More)
The note describes the Recognizing Textual Entailment (RTE) system developed at the Computer Science and Engineering Department, Jadavpur University, India. In this competition, we have participated and submitted the results in the RTE-7 Main Task (3 runs), Novelty Task (3 runs) and RTE-7 KBP Validation task (2 unique runs for generic task and 2 unique runs(More)
Abstr act. The article presents the experiments carried out as part of the participation in the Paragraph Selection (PS) Task and Answer Selection (AS) Task of QA@CLEF 2010 – ResPubliQA. Our System use Apache Lucene for document retrieval system. All test documents are indexed using Apache Lucene. Stop words are removed from each question and query words(More)
This paper presents the experiments carried out at Jadavpur University as part of the participation in the Forum for Information Retrieval Evaluation (FIRE) 2010 in ad-hoc mono-lingual information retrieval task for English and Bengali languages. The experiments carried out by us for FIRE 2010 are based on stemming, zonal indexing, theme identification,(More)