Events are happening in real world and time, which can be planned organized for occasions, such as social gatherings, festival celebrations, influential meetings, or sports activities. Social media platforms generate a lot of real-time text information regarding public events with different topics. However, mining is challenging because typically exhibit heterogeneous texture metadata often amb...

ion power of a logic programming language to do grouping. Hence it has support for intentional and extensional grouping, which is used to express design patterns and software architectures. Because of its integration with Smalltalk, the model is extensible. When the model needs to encompass new kinds of entities, only some reification rules have to be added to make those entities explicit in SO...

This paper overviews BUPTTeam’s participation in the main task organized within the RTE7 Evaluation. In this paper we propose a method to calculate the similarity between text and hypothesis based on the TF/IDF values. Our system designed to recognize textual entailment typically employ lexical information. The evaluation results show that our method is effective for RTE task.

This paper proposes a general probabilistic setting that formalizes a probabilistic notion of textual entailment. We further describe a particular preliminary model for lexical-level entailment, based on document cooccurrence probabilities, which follows the general setting. The model was evaluated on two application independent datasets, suggesting the relevance of such probabilistic approache...

We propose a domain specific Question Answering system. We deviate from approaching this problem as a Textual Entailment task. We implemented a Memory Network-based Question Answering system which test a Machine’s understanding of legal text and identifies whether an answer to a question is correct or wrong, given some background knowledge. We also prepared a corpus of real USA MBE Bar exams fo...

We participated in Japanese tasks of RITE in NTCIR9 (team id: “KYOTO”). Our proposed method regards predicateargument structure as a basic unit of handling the meaning of text/hypothesis, and performs the matching between text and hypothesis. Our system first performs predicateargument structure analysis to both a text and a hypothesis. Then, we perform the matching between text and hypothesis....

This paper presents a machine-learning approach for the recognition of textual entailment. For our approach we model lexical and semantic features. We study the effect of stacking and voting joint classifier combination techniques which boost the final performance of the system. In an exhaustive experimental evaluation, the performance of the developed approach is measured. The obtained results...

We address two challenges for automatic machine translation evaluation: a) avoiding the use of reference translations, and b) focusing on adequacy estimation. From an economic perspective, getting rid of costly hand-crafted reference translations (a) permits to alleviate the main bottleneck in MT evaluation. From a system evaluation perspective, pushing semantics into MT (b) is a necessity in o...