Algorithm 447: efficient algorithms for graph manipulation
Communications of the ACM
Accurate methods for the statistics of surprise and coincidence
Computational Linguistics - Special issue on using large corpora: I
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Information extraction from unstructured web text
Information extraction from unstructured web text
Type nanotheories: a framework for term comparison
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Mining functional dependencies from data
Data Mining and Knowledge Discovery
It's a contradiction---no, it's not: a case study using functional relations
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Scaling textual inference to the web
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Unsupervised methods for determining object and relation synonyms on the web
Journal of Artificial Intelligence Research
Open information extraction from the web
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
A probabilistic model of redundancy in information extraction
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Quantifier scope disambiguation using extracted pragmatic knowledge: preliminary results
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 3 - Volume 3
A latent dirichlet allocation method for selectional preferences
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning arguments and supertypes of semantic relations using recursive patterns
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Learning first-order Horn clauses from web text
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Automatic evaluation of ontologies (AEON)
ISWC'05 Proceedings of the 4th international conference on The Semantic Web
Identifying relations for open information extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Open information extraction: the second generation
IJCAI'11 Proceedings of the Twenty-Second international joint conference on Artificial Intelligence - Volume Volume One
Dependency-based open information extraction
ROBUS-UNSUP '12 Proceedings of the Joint Workshop on Unsupervised and Semi-Supervised Learning in NLP
Identifying constant and unique relations by using time-series text
EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
Rule-based opinion target and aspect extraction to acquire affective knowledge
Proceedings of the 22nd international conference on World Wide Web companion
Aggregated search: A new information retrieval paradigm
ACM Computing Surveys (CSUR)
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Determining whether a textual phrase denotes a functional relation (i.e., a relation that maps each domain element to a unique range element) is useful for numerous NLP tasks such as synonym resolution and contradiction detection. Previous work on this problem has relied on either counting methods or lexico-syntactic patterns. However, determining whether a relation is functional, by analyzing mentions of the relation in a corpus, is challenging due to ambiguity, synonymy, anaphora, and other linguistic phenomena. We present the Leibniz system that overcomes these challenges by exploiting the synergy between the Web corpus and freely-available knowledge resources such as Free-base. It first computes multiple typed functionality scores, representing functionality of the relation phrase when its arguments are constrained to specific types. It then aggregates these scores to predict the global functionality for the phrase. Leibniz outperforms previous work, increasing area under the precision-recall curve from 0.61 to 0.88. We utilize Leibniz to generate the first public repository of automatically-identified functional relations.