M. Nissim

Publications
Influence

Exploiting Context for Biomedical Entity Recognition: From Syntax to the Web

Jenny Rose Finkel, S. Dingare, Huy Nguyen, M. Nissim, Christopher D. Manning, G. Sinclair
Computer Science
NLPBA/BioNLP
28 August 2004

We describe a machine learning system for the recognition of names in biomedical texts. Expand

An Annotation Scheme for Information Status in Dialogue

M. Nissim, S. Dingare, J. Carletta, Mark Steedman
Computer Science
LREC
1 May 2004

We present an annotation scheme for information status (IS) in dialogue, and validate it on three Switchboard dialogues. Expand

The Meaning Factory: Formal Semantics for Recognizing Textual Entailment and Determining Semantic Similarity

Johannes Bjerva, Johan Bos, Rob van der Goot, M. Nissim
Computer Science
SemEval@COLING
1 August 2014

Shared Task 1 of SemEval-2014 comprised two subtasks on the same dataset of sentence pairs: recognizing textual entailment and determining textual similarity. Expand

N-GrAM: New Groningen Author-profiling Model

Angelo Basile, G. Dwyer, M. Medvedeva, J. Rawee, Hessel Haagsma, M. Nissim
Computer Science
CLEF
12 July 2017

We describe our participation in the PAN 2017 shared task on Author Profiling, identifying authors’ gender and language variety for English, Spanish, Arabic and Portuguese. Expand

Using the Web for Nominal Anaphora Resolution

K. Markert, M. Nissim, Natalia N. Modjeska
Computer Science
2003

We present a novel method for resolving non-pronominal anaphora. Instead of using handcrafted lexical resources, we search the Web with shallow patterns which can be predetermined for the type of… Expand

Exploring the boundaries: gene and protein identification in biomedical text

Jenny Rose Finkel, S. Dingare, Christopher D. Manning, M. Nissim, Beatrice Alex, C. Grover
Computer Science, Medicine
BMC Bioinformatics
24 May 2005

We present a maximum-entropy based system incorporating a diverse set of features for identifying gene and protein names in biomedical abstracts.ResultsThis system was entered in the BioCreative comparative evaluation and achieved a precision of 0.84 in the "open" evaluation and a recall of 99% in the closed evaluation. Expand

Sentiment analysis on Italian tweets

Valerio Basile, M. Nissim
Computer Science
WASSA@NAACL-HLT
14 June 2013

We describe TWITA, the first corpus of Italian tweets, which is created via a completely automatic procedure, portable to any other language. Expand

Syntactic Features and Word Similarity for Supervised Metonymy Resolution

M. Nissim, K. Markert
Computer Science
ACL
7 July 2003

We show that syntactic head-modifier relations are a high precision feature for metonymy recognition but suffer from data sparseness. Expand

Towards a Corpus Annotated for Metonymies: the Case of Location Names

K. Markert, M. Nissim
Computer Science
LREC
1 May 2002

We present a framework for annotating metonymies in domain-independent text that considers the regularity, productivity and underspecification of metonymic usage. Expand

Adding Semantics to Data-Driven Paraphrasing

Ellie Pavlick, Johan Bos, M. Nissim, Charley Beller, Benjamin Van Durme, Chris Callison-Burch
Computer Science
ACL
1 July 2015

We add an interpretable semantics to the paraphrase database (PPDB). Expand

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