Meni Adler


2017

pdf bib
A Consolidated Open Knowledge Representation for Multiple Texts
Rachel Wities | Vered Shwartz | Gabriel Stanovsky | Meni Adler | Ori Shapira | Shyam Upadhyay | Dan Roth | Eugenio Martinez Camara | Iryna Gurevych | Ido Dagan
Proceedings of the 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-level Semantics

We propose to move from Open Information Extraction (OIE) ahead to Open Knowledge Representation (OKR), aiming to represent information conveyed jointly in a set of texts in an open text-based manner. We do so by consolidating OIE extractions using entity and predicate coreference, while modeling information containment between coreferring elements via lexical entailment. We suggest that generating OKR structures can be a useful step in the NLP pipeline, to give semantic applications an easy handle on consolidated information across multiple texts.

pdf bib
Interactive Abstractive Summarization for Event News Tweets
Ori Shapira | Hadar Ronen | Meni Adler | Yael Amsterdamer | Judit Bar-Ilan | Ido Dagan
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing: System Demonstrations

We present a novel interactive summarization system that is based on abstractive summarization, derived from a recent consolidated knowledge representation for multiple texts. We incorporate a couple of interaction mechanisms, providing a bullet-style summary while allowing to attain the most important information first and interactively drill down to more specific details. A usability study of our implementation, for event news tweets, suggests the utility of our approach for text exploration.

2016

pdf bib
Specifying and Annotating Reduced Argument Span Via QA-SRL
Gabriel Stanovsky | Ido Dagan | Meni Adler
Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)

2015

pdf bib
Multi-Level Alignments As An Extensible Representation Basis for Textual Entailment Algorithms
Tae-Gil Noh | Sebastian Padó | Vered Shwartz | Ido Dagan | Vivi Nastase | Kathrin Eichler | Lili Kotlerman | Meni Adler
Proceedings of the Fourth Joint Conference on Lexical and Computational Semantics

2012

pdf bib
Efficient Tree-based Approximation for Entailment Graph Learning
Jonathan Berant | Ido Dagan | Meni Adler | Jacob Goldberger
Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)

pdf bib
Entailment-based Text Exploration with Application to the Health-care Domain
Meni Adler | Jonathan Berant | Ido Dagan
Proceedings of the ACL 2012 System Demonstrations

2009

pdf bib
Enhancing Unlexicalized Parsing Performance Using a Wide Coverage Lexicon, Fuzzy Tag-Set Mapping, and EM-HMM-Based Lexical Probabilities
Yoav Goldberg | Reut Tsarfaty | Meni Adler | Michael Elhadad
Proceedings of the 12th Conference of the European Chapter of the ACL (EACL 2009)

2008

pdf bib
Unsupervised Lexicon-Based Resolution of Unknown Words for Full Morphological Analysis
Meni Adler | Yoav Goldberg | David Gabay | Michael Elhadad
Proceedings of ACL-08: HLT

pdf bib
EM Can Find Pretty Good HMM POS-Taggers (When Given a Good Start)
Yoav Goldberg | Meni Adler | Michael Elhadad
Proceedings of ACL-08: HLT

pdf bib
Tagging a Hebrew Corpus: the Case of Participles
Meni Adler | Yael Netzer | Yoav Goldberg | David Gabay | Michael Elhadad
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)

We report on an effort to build a corpus of Modern Hebrew tagged with part-of-speech and morphology. We designed a tagset specific to Hebrew while focusing on four aspects: the tagset should be consistent with common linguistic knowledge; there should be maximal agreement among taggers as to the tags assigned to maintain consistency; the tagset should be useful for machine taggers and learning algorithms; and the tagset should be effective for applications relying on the tags as input features. In this paper, we illustrate these issues by explaining our decision to introduce a tag for beinoni forms in Hebrew. We explain how this tag is defined, and how it helped us improve manual tagging accuracy to a high-level, while improving automatic tagging and helping in the task of syntactic chunking.

2007

pdf bib
Can You Tag the Modal? You Should.
Yael Netzer | Meni Adler | David Gabay | Michael Elhadad
Proceedings of the 2007 Workshop on Computational Approaches to Semitic Languages: Common Issues and Resources

2006

pdf bib
An Unsupervised Morpheme-Based HMM for Hebrew Morphological Disambiguation
Meni Adler | Michael Elhadad
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics

pdf bib
Noun Phrase Chunking in Hebrew: Influence of Lexical and Morphological Features
Yoav Goldberg | Meni Adler | Michael Elhadad
Proceedings of the 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics