We implemented a baseline approach to why-question answering based on paragraph retrieval. Our implementation incorporates the QAP ranking algorithm with addition of a number of surface features (cue words and XML markup). With this baseline system, we obtain an accuracy-at-10 of 57.0% with an MRR of 0.31. Both the baseline and the proposed evaluation method are good starting points for the cur...

We consider the problem of adapting neural paragraph-level question answering models to the case where entire documents are given as input. Our proposed solution trains models to produce well calibrated confidence scores for their results on individual paragraphs. We sample multiple paragraphs from the documents during training, and use a sharednormalization training objective that encourages t...

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 are identified to retrieve the most rele...

2. paragraph 1: to areas with lack of psychiatrists -> to areas which lack psychiatrists or to areas with a lack of psychiatrists OK 3. paragraph 1: I believe the use of 'situations characterised by uncertainty' should be omitted from abstract or put in a separate sentence We have omitted this part of the sentence. 4. paragraph 3: I believe the use of 'also when VC is not used' should be omitte...

This supplement is organized as follows: • Section 1 clarifies assumptions (main paper, Section 4, first paragraph). • Section 2 describes the plane principal method used for normal smoothing (main paper, Section 4.1, first paragraph). • Section 3 pertains to the optimization program and includes a simulation (main paper, Section 4.2.2). • Section 4 shows a qualitative comparison to a multi-str...

Natural language processing and statistical methods were used to identify linguistic features associated with the quality of student-generated paragraphs. Linguistic features were assessed using Coh-Metrix. The resulting computational models demonstrated small to medium effect sizes for predicting paragraph quality: introduction quality r2 = .25, body quality r2 = .10, and conclusion quality r2...