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  • Influence
The Stanford CoreNLP Natural Language Processing Toolkit
TLDR
The design and use of the Stanford CoreNLP toolkit is described, an extensible pipeline that provides core natural language analysis, and it is suggested that this follows from a simple, approachable design, straightforward interfaces, the inclusion of robust and good quality analysis components, and not requiring use of a large amount of associated baggage. Expand
Multi-instance Multi-label Learning for Relation Extraction
TLDR
This work proposes a novel approach to multi-instance multi-label learning for RE, which jointly models all the instances of a pair of entities in text and all their labels using a graphical model with latent variables that performs competitively on two difficult domains. Expand
The CoNLL 2008 Shared Task on Joint Parsing of Syntactic and Semantic Dependencies
TLDR
This shared task not only unifies the shared tasks of the previous four years under a unique dependency-based formalism, but also extends them significantly: this year's syntactic dependencies include more information such as named-entity boundaries; the semantic dependencies model roles of both verbal and nominal predicates. Expand
Deterministic Coreference Resolution Based on Entity-Centric, Precision-Ranked Rules
TLDR
The two stages of the sieve-based architecture, a mention detection stage that heavily favors recall, followed by coreference sieves that are precision-oriented, offer a powerful way to achieve both high precision and high recall. Expand
The CoNLL-2009 Shared Task: Syntactic and Semantic Dependencies in Multiple Languages
TLDR
This shared task combines the shared tasks of the previous five years under a unique dependency-based formalism similar to the 2008 task and describes how the data sets were created and show their quantitative properties. Expand
Stanford’s Multi-Pass Sieve Coreference Resolution System at the CoNLL-2011 Shared Task
TLDR
The coreference resolution system submitted by Stanford at the CoNLL-2011 shared task was ranked first in both tracks, with a score of 57.8 in the closed track and 58.3 in the open track. Expand
A Multi-Pass Sieve for Coreference Resolution
TLDR
This work proposes a simple coreference architecture based on a sieve that applies tiers of deterministic coreference models one at a time from highest to lowest precision, and outperforms many state-of-the-art supervised and unsupervised models on several standard corpora. Expand
Using Predicate-Argument Structures for Information Extraction
TLDR
The experimental results prove the claim that accurate predicate-argument structures enable high quality IE results, and introduce a new way of automatically identifying predicate argument structures, which is central to the IE paradigm. Expand
Joint Entity and Event Coreference Resolution across Documents
TLDR
A novel coreference resolution system that models entities and events jointly that handles nominal and verbal events as well as entities, and the joint formulation allows information from event coreference to help entity coreference, and vice versa. Expand
FALCON: Boosting Knowledge for Answer Engines
TLDR
FALCON, an answer engine that integrates different forms of syntactic, semantic and pragmatic knowledge for the goal of achieving better performance is discussed. Expand
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