| c |
| COLIEE | Analyzable Legal Yes/No Question Answering System using Linguistic Structures
Legal Question Answering System using Neural Attention |
| d |
| deep learning | Recognizing entailments in legal texts using sentence encoding-based and decomposable attention models |
| distributional semantics | Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities |
| e |
| Ensemble approach | A Civil Code Article Information Retrieval System based on Phrase Alignment with Article Structure Analysis and Ensemble Approach |
| entailment extraction | Recognizing entailments in legal texts using sentence encoding-based and decomposable attention models |
| h |
| hybrid method for RTE | Multiple Agent Based Entailment System(MABES) for RTE |
| i |
| Information Retrieval | Overview of COLIEE 2017
A Civil Code Article Information Retrieval System based on Phrase Alignment with Article Structure Analysis and Ensemble Approach
Recognizing entailments in legal texts using sentence encoding-based and decomposable attention models
Legal Information Retrieval Using Topic Clustering and Neural Networks |
| j |
| Japanese civil code | A Civil Code Article Information Retrieval System based on Phrase Alignment with Article Structure Analysis and Ensemble Approach |
| juris-informatics | Overview of COLIEE 2017 |
| l |
| language modeling | Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities |
| Legal Bar Exam | Legal Question Answering System using Neural Attention |
| Legal Document Processing | Overview of COLIEE 2017
Analyzable Legal Yes/No Question Answering System using Linguistic Structures |
| legal entailment | Multiple Agent Based Entailment System(MABES) for RTE |
| legal information retrieval | Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities |
| legal knowledge base | Multiple Agent Based Entailment System(MABES) for RTE |
| Legal Question Answering | Recognizing entailments in legal texts using sentence encoding-based and decomposable attention models |
| n |
| Natural Language Processing | Analyzable Legal Yes/No Question Answering System using Linguistic Structures |
| negation rule | Multiple Agent Based Entailment System(MABES) for RTE |
| neural networks | Legal Information Retrieval Using Topic Clustering and Neural Networks |
| p |
| Phrase matching | A Civil Code Article Information Retrieval System based on Phrase Alignment with Article Structure Analysis and Ensemble Approach |
| q |
| Question Answering | Overview of COLIEE 2017
Legal Question Answering System using Neural Attention |
| r |
| recognition textual entailment | Multiple Agent Based Entailment System(MABES) for RTE |
| Recognizing Textual Entailment | Legal Question Answering System using Neural Attention |
| RTE | Multiple Agent Based Entailment System(MABES) for RTE |
| s |
| similarity | Multiple Agent Based Entailment System(MABES) for RTE |
| syntactic analysis | Multiple Agent Based Entailment System(MABES) for RTE |
| t |
| Term Order Probabilities | Improving Legal Information Retrieval by Distributional Composition with Term Order Probabilities |
| Textual Entailment | Overview of COLIEE 2017
Legal Information Retrieval Using Topic Clustering and Neural Networks |
| topic clustering | Legal Information Retrieval Using Topic Clustering and Neural Networks |
| y |
| Yes/No Question Answering | Analyzable Legal Yes/No Question Answering System using Linguistic Structures |
