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Context Dependent Claim Detection
- Ran Levy, Yonatan Bilu, Daniel Hershcovich, E. Aharoni, N. Slonim
- Computer ScienceCOLING
- 1 August 2014
This work formally defines the challenging task of automatic claim detection in a given context and outlines a preliminary solution, and assess its performance over annotated real world data, collected specifically for that purpose over hundreds of Wikipedia articles.
A Benchmark Dataset for Automatic Detection of Claims and Evidence in the Context of Controversial Topics
A novel and unique argumentative structure dataset that consists of data extracted from hundreds of Wikipedia articles using a meticulously monitored manual annotation process, organized under a simp le claim-evidence structure.
A Transition-Based Directed Acyclic Graph Parser for UCCA
This work presents the first parser for UCCA, a cross-linguistically applicable framework for semantic representation, which builds on extensive typological work and supports rapid annotation and its ability to handle more general graph structures can inform the development of parsers for other semantic DAG structures, and in languages that frequently use discontinuous structures.
SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA
- Daniel Hershcovich, Zohar Aizenbud, Leshem Choshen, Elior Sulem, A. Rappoport, Omri Abend
- Computer Science*SEMEVAL
- 6 March 2019
The SemEval 2019 shared task on Universal Conceptual Cognitive Annotation parsing in English, German and French is presented, and the participating systems and results are discussed.
MRP 2019: Cross-Framework Meaning Representation Parsing
The 2019 Shared Task at the Conference for Computational Language Learning (CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks. Five distinct approaches to the…
Multitask Parsing Across Semantic Representations
It is shown that multitask learning significantly improves UCCA parsing in both in-domain and out-of-domain settings, and uniform transition-based system and learning architecture for all parsing tasks are experiment on.
MRP 2020: The Second Shared Task on Cross-Framework and Cross-Lingual Meaning Representation Parsing
The 2020 Shared Task at the Conference for Computational Language Learning (CoNLL) was devoted to Meaning Representation Parsing (MRP) across frameworks and languages. Extending a similar setup from…
Automatic Claim Negation: Why, How and When
This work asks how this set of detected claims can be augmented further, by adding to it the negation of each detected claim, presenting two NLP problems: how to automatically negate a claim, and when such a negated claim can plausibly be used.
TUPA at MRP 2019: A Multi-Task Baseline System
The TUPA system submission to the shared task on Cross-Framework Meaning Representation Parsing (MRP) at the 2019 Conference for Computational Language Learning (CoNLL) provides a baseline point of comparison and is not considered in the official ranking of participating systems.
Multilingual Compositional Wikidata Questions
This work proposes a method for creating a multilingual, parallel dataset of question-query pairs, grounded in Wikidata, and introduces such a dataset called CompositionalWikidata Questions (CWQ), and utilizes this data to train and evaluate semantic parsers for Hebrew, Kannada, Chinese and English, to better understand the current strengths and weaknesses of multilingual semantic parsing.